Clone_validation_tutorial.ipynb

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      "source": [
        "<a href=\"https://colab.research.google.com/github/epi2me-labs/tutorials/blob/master/Clone_validation_tutorial.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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      "source": [
        "<h1>Validation of cloned DNA material using Nanopore sequencing</h1>\n",
        "\n",
        "The workflow below is intended to assess a molecular cloning experiment, specifically whether the introduction of one sequence into another has been successful. For example, the introduction of a protein encoding sequence into a plasmid vector molecule.\n",
        "\n",
        "Questions answered by this tutorial include:\n",
        "\n",
        "* If a barcoding strategy has been used, what fraction of demultiplexed reads\n",
        "correspond to the target of interest.\n",
        "* Does a sequenced DNA construct correspond to its expected sequence? \n",
        "* Does the sequenced DNA construct contain frameshifts or base substitions?\n",
        "* If the DNA construct encodes a peptide sequence, is the peptide sequence correct?\n",
        "\n",
        "Methods used in this tutorial include:\n",
        "\n",
        "* `guppy_barcoder` for the demultiplexing of barcoded sequence reads,\n",
        "* `mini_align` from the `pomoxis` package is used to align sequence reads to the target sequence of interest, and\n",
        "* `flye` is used to assemble the input sequencing reads,\n",
        "\n",
        "Computational requirements for this tutorial:\n",
        "\n",
        "* A computer running the **EPI2ME Labs** server\n",
        "* 16Gb RAM\n",
        "\n",
        "> ⚠️ **Warning:** This notebook has been saved with its outputs for demostration purposed. It is recommeded to select `Edit > Clear all outputs` before using the notebook to analyse your own data.\n",
        "\n"
      ]
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      "cell_type": "markdown",
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      "source": [
        "## Introduction\n",
        "\n",
        "This tutorial aims to determine the success of a molecular cloning experiment; to determine whether one DNA sequence has been correctly inserted into another as the experimentalist was expecting.\n",
        "\n",
        "The goals from this tutorial include:\n",
        "\n",
        "* Understand how to perform basic QC steps on the input data.\n",
        "* Know how to assess the circularisation of a sequence assembly.\n",
        "* Verify that the required sequence has been correctly inserted into the target."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "VWIv_lakSnbh",
        "colab_type": "text"
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      "source": [
        "This workflow naturally requires knowledge of the target sequence and optionally its encoded peptide. The methodology presented is based on an sequence assembly method; an alternative simpler method would be to employ simple sequence alignment."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ZMhjoLNaP6Ku",
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      "source": [
        "## Getting started\n",
        "\n",
        "The workflow below requires a single folder containing .fastq files from an Oxford Nanopore Technologies' sequencing device, or a single such file. Compressed or uncompressed files may be used. In addition a DNA reference sequences for the vector is required, and a protein reference sequence for the inserted DNA sequence.\n",
        "\n",
        "Before anything else we will create and set a working directory:"
      ]
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          "height": 34
        },
        "outputId": "1bb1ff9b-ca9c-4390-9c96-3b91fbd19183"
      },
      "source": [
        "from epi2melabs import ping\n",
        "tutorial_name = \"clone_validation\"\n",
        "pinger = ping.Pingu()\n",
        "pinger.send_notebook_ping('start', tutorial_name)\n",
        "\n",
        "# create a work directory and move into it\n",
        "working_dir = '/epi2melabs/{}/'.format(tutorial_name)\n",
        "!mkdir -p \"$working_dir\"\n",
        "%cd \"$working_dir\""
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/epi2melabs/clone_validation\n"
          ],
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        }
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      "cell_type": "markdown",
      "metadata": {
        "id": "v4aBV-9WYUg2",
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      },
      "source": [
        "### Install additional software\n",
        "\n",
        "This tutorial uses a couple of software packages that are not included in the default **EPI2ME Labs** server. Below we will install software packages that include `last` and `diamond` using the `conda` package manager. \n",
        "\n",
        "*Please note that the software installed is not persistent and this step will need to be re-run if you stop and restart the EPI2ME Labs server*"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xQHDlPsOZABt",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "!mamba install -y -q -c bioconda last diamond"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "v5uwBJCVECBg",
        "colab_type": "text"
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      "source": [
        "### Sample Data\n",
        "\n",
        "To demonstrate the workflow below a sample dataset is included with this tutorial. The dataset comprises data from a small Flongle sequencing experiment together with a vector DNA sequence and target gene protein sequence.\n",
        "\n",
        "To download the sample file we run the `linux` command `wget`. To execute the command click on the cell and then press Command/Ctrl-Enter, or click the Play symbol to the left-hand side."
      ]
    },
    {
      "cell_type": "code",
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          "height": 309
        },
        "outputId": "330799f6-0853-4530-ee28-b5e1ca346037"
      },
      "source": [
        "bucket = \"ont-exd-int-s3-euwst1-epi2me-labs\"\n",
        "domain = \"s3-eu-west-1.amazonaws.com\"\n",
        "site = \"https://{}.{}\".format(bucket, domain)\n",
        "\n",
        "!rm -rf clone_sample_data clone_sample_data.tar.gz\n",
        "!wget -O clone_sample_data.tar.gz \\\n",
        "    \"$site/$tutorial_name/clone_sample_data.tar.gz\"\n",
        "!tar -xzvf clone_sample_data.tar.gz"
      ],
      "execution_count": 4,
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            "--2020-07-30 14:17:25--  https://ont-exd-int-s3-euwst1-epi2me-labs.s3-eu-west-1.amazonaws.com/clone_validation/clone_sample_data.tar.gz\r\n",
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            "\n",
            "2020-07-30 14:17:26 (40.3 MB/s) - ‘clone_sample_data.tar.gz’ saved [20287766/20287766]\n",
            "\n",
            "clone_sample_data/\n",
            "clone_sample_data/flongle_clone_data.fastq.gz\n",
            "clone_sample_data/peptide2.fasta\n",
            "clone_sample_data/vector.fasta\n",
            "clone_sample_data/peptide1.fasta\n"
          ],
          "name": "stdout"
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      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "B1n24GGRRBk1",
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      "source": [
        "The dataset contains four files. One of these (`flone_clone_data.fastq.gz`) is a small set of single-molecule sequencing reads from a Flongle flowcell. The reads comprise five multiplexed samples. For two of these samples (barcodes 01 and 02) the dataset contains the target peptides: `peptide1.fasta` and `peptide2.fasta` respectively. These have been successfully incorporated into the vector sequence `vector.fasta`, as the workflow will show."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "nh7-4mZeXHRA",
        "colab_type": "text"
      },
      "source": [
        "### Using your own data\n",
        "\n",
        "If you have your own sequencing, you can edit the value of the input variables below in the **Data Entry** section. To find the correct full path of a file you can navigate to it in the **Files** browser to the left-hand side, right-click on the file and select **Copy path**:"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "vDCEs7E3Zy60",
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      "source": [
        "![image.png](data:image/png;base64,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)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "h43P8CBYzV0e",
        "colab_type": "text"
      },
      "source": [
        "The location shared with the EPI2ME labs server from your computer will show as `/epi2melabs`, for example a file located at `/data/my_gridion_run/fastq_pass` on your computer will appear as `/epi2melabs/my_gridion_run/fastq_pass` when it is the `/data` folder that is shared."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "1VM9k1NGZ8co",
        "colab_type": "text"
      },
      "source": [
        "### Data entry\n",
        "\n",
        "Having downloaded the sample data, or locating your own data in the file browser, we need to provide the filepaths as input to the notebook.\n",
        "\n",
        "The form can be used to enter the filenames of your inputs. Alternatively you can edit the code which reads the inputs by first double clicking the form header. After entering your inputs (or editing the code cell) remember to execute the code using `Command/Ctrl-Enter`, or pressing the `Play` symbol to the left-hand side."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "46QEClv31y4J",
        "colab_type": "text"
      },
      "source": [
        ">**This workflow requires has some manual intervention steps to check the sanity of intermediate outputs. It is not recommended to use the `Run All` functionality.**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hexEX4x8VPfA",
        "colab_type": "code",
        "cellView": "form",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 119
        },
        "outputId": "9cee0fb1-be77-4b74-a732-df15365a9290"
      },
      "source": [
        "#@markdown Enter the path to your input files (*click **here** to view code*)\n",
        "\n",
        "#@markdown The `input_reads` item may be a single folder containing .fastq files from an Oxford Nanopore Technologies' sequencing device, or a single such file. \n",
        "\n",
        "import aplanat\n",
        "from aplanat.graphics import InfoGraphItems\n",
        "from aplanat.report import HTMLReport\n",
        "import pandas as pd\n",
        "import os\n",
        "\n",
        "bashgreen = r\"\\e[1m\\e[32m\"\n",
        "bashred = r\"\\e[1m\\e[31m\"\n",
        "bashdefault = r\"\\e[0m\\e[39m\"\n",
        "\n",
        "# set variables for our inputs\n",
        "input_reads = 'clone_sample_data/flongle_clone_data.fastq.gz'  #@param {type: \"string\"}\n",
        "output_folder = 'analysis'  #@param {type: \"string\"}\n",
        "target_dna_sequence = 'clone_sample_data/vector.fasta' #@param {type: \"string\"}\n",
        "target_peptide = 'clone_sample_data/peptide1.fasta' #@param {type: \"string\"}\n",
        "threads = 8 #@param {type: \"integer\"}\n",
        "demultiplex = True #@param {type: \"boolean\"}\n",
        "samples_analysed = dict()\n",
        "\n",
        "print(\"Checking read inputs...\")\n",
        "fail_msg = \"The input read file is not a valid file or folder.\"\n",
        "if os.path.isdir(input_reads):\n",
        "    print(\"Found input folder.\")\n",
        "elif os.path.isfile(input_reads):\n",
        "    print(\"Found input file, moving to a folder\")\n",
        "    # guppy demultiplexer takes only an input folder\n",
        "    fname = os.path.basename(input_reads)\n",
        "    !mkdir -p reads \\\n",
        "        && mv $input_reads reads\n",
        "    input_reads = os.path.abspath(\"reads\")\n",
        "elif os.path.isdir('reads'):\n",
        "    moved_file = os.path.join('reads', os.path.basename(input_reads))\n",
        "    if os.path.isfile(moved_file):\n",
        "        input_reads = os.path.abspath(\"reads\")\n",
        "        print(\"Found previously moved file.\")\n",
        "    else:\n",
        "        raise IOError(fail_msg)\n",
        "else:\n",
        "    raise IOError(fail_msg)\n",
        "print(\"Input reads is: {}.\".format(input_reads))\n",
        "print(\"Making output folder...\")\n",
        "!mkdir -p output_folder\n",
        "print(\"Checking reference inputs...\")\n",
        "if not os.path.isfile(target_dna_sequence):\n",
        "    print(\"Target sequence file does not exist.\")\n",
        "if not os.path.isfile(target_peptide):\n",
        "    print(\"Target peptide file does not exist.\")\n",
        "print(\"Done.\")\n",
        "\n",
        "report = HTMLReport(\n",
        "    \"Nanopore Clone Validation workflow\", \"EPI2ME Labs Summary\",\n",
        "    require_keys=True)\n",
        "report.markdown('### Experiment Summary', 'exp-summ-head')\n",
        "report.placeholder(key='exec-plot')  # placeholder\n",
        "exec_summary = InfoGraphItems()\n"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Checking read inputs...\n",
            "Found input file, moving to a folder\n",
            "Input reads is: /epi2melabs/clone_validation/reads.\n",
            "Making output folder...\n",
            "Checking reference inputs...\n",
            "Done.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ZegHRkre91c0",
        "colab_type": "text"
      },
      "source": [
        "With our workspace prepared we will now move on to the analysis of our data."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "b1a0pqln1FLz",
        "colab_type": "text"
      },
      "source": [
        "### Preliminary Analysis Section\n",
        "\n",
        "It is likely that multiple DNA constructs will have been barcoded and run in parallel during a sequencing run. For this reason we include an optional barcode **demultiplexing** step in this workflow.\n",
        "\n",
        "> After demultiplexing, this notebook is concerned with only a single sample. To analyse all samples the later sections of this notebook will need to be run sequentially. The results of analysing each of the samples will be accumulated into a report which can be downloaded at the end of the notebook.\n",
        "\n",
        "If a barcoding strategy has not been used within your experiment, this step can be skipped."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2-smxqO-JbnZ",
        "colab_type": "code",
        "cellView": "form",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 289
        },
        "outputId": "277a7dc5-f082-43de-ecc1-6929291be6ca"
      },
      "source": [
        "#@markdown **Running Guppy demultiplexing** *(press play)*\n",
        "barcode_kit = \"SQK-RBK004\" #@param {type: \"string\"}\n",
        "\n",
        "!rm -rf $output_folder/demultiplex\n",
        "if demultiplex:\n",
        "    !guppy_barcoder \\\n",
        "        --barcode_kits $barcode_kit \\\n",
        "        --compress_fastq --records_per_fastq 0 --recursive --worker_threads $threads \\\n",
        "        --save_path $output_folder/demultiplex \\\n",
        "        --input_path $input_reads \\\n",
        "        && echo \"$bashgreen\"Guppy finished successfully\"$bashdefault\" \\\n",
        "        || echo \"$bashred\"Guppy failed\"$bashdefault\"\n",
        "else:\n",
        "    print(\"Skipping demultiplexing as requested.\")\n"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "\n",
            "ONT Guppy barcoding software version 3.5.2+5b7a51b\n",
            "input path:         /epi2melabs/clone_validation/reads\n",
            "save path:          analysis/demultiplex\n",
            "arrangement files:  barcode_arrs_rbk4.cfg \n",
            "min. score front:   60\n",
            "min. score rear:    60\n",
            "\n",
            "\n",
            "Found 1 fastq files.\n",
            "\n",
            "0%   10   20   30   40   50   60   70   80   90   100%\n",
            "|----|----|----|----|----|----|----|----|----|----|\n",
            "***************************************************\n",
            "Done in 540 ms.\n",
            "\\e[1m\\e[32mGuppy finished successfully\\e[0m\\e[39m\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "keFTrRWr84xW",
        "colab_type": "text"
      },
      "source": [
        "Having run demultiplexing of reads below code cell will allow you to view the number of reads found to contain each barcode and allow you to select which group of reads to use in the remainder of the workflow. If you have not run demultiplexing the code will set parameters for the workflow. *It is necessary to run this step even in the case of a single (unbarcoded) analyte.*"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "t8nvVfVxzc1X",
        "colab_type": "code",
        "cellView": "form",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 366,
          "referenced_widgets": [
            "64e8f4fd7e5f470b8f901a8fb18c6f4c",
            "740b2a7bc06941f0891df59820497692",
            "a780134481db4c76b65359e162da03a9"
          ]
        },
        "outputId": "1646b5b8-eb26-412d-b43f-e824fc3029ac"
      },
      "source": [
        "#@markdown **Review demultiplex barcode assignments** *(click to show)*\n",
        "\n",
        "import ipywidgets as widgets\n",
        "from IPython.display import display\n",
        "\n",
        "import aplanat\n",
        "from aplanat import bars, hist, annot\n",
        "from bokeh.models import Span\n",
        "from bokeh.layouts import gridplot\n",
        "\n",
        "minimum_reads = 150\n",
        "read_source = None\n",
        "complete_fastq = None\n",
        "dataset_name = None\n",
        "dataset_folder = None\n",
        "\n",
        "barcodes_found = 'NA'\n",
        "\n",
        "if not demultiplex:\n",
        "    read_source = input_reads\n",
        "    dataset_name = 'all_data'\n",
        "    dataset_folder = os.path.join(output_folder, dataset_name)\n",
        "    complete_fastq = os.path.join(dataset_folder, \"all_data.fastq\")\n",
        "    barcodes_found = 'NA'\n",
        "else:\n",
        "    barcode_summary_file = os.path.join(\n",
        "        output_folder, \"demultiplex\", \"barcoding_summary.txt\")\n",
        "    if not os.path.exists(barcode_summary_file):\n",
        "        print(\"Could not find barcode summary: {}.\".format(barcode_summary_file))\n",
        "    else:\n",
        "        try:\n",
        "            bc_summary = pd.read_csv(barcode_summary_file, sep='\\t')\n",
        "        except Exception as e:\n",
        "            print(\"Could not read barcode summary: {}\".format(barcode_summary))\n",
        "    \n",
        "    # barcode count plot\n",
        "    barcode_counts = pd.DataFrame(bc_summary['barcode_arrangement'].value_counts()) \\\n",
        "        .sort_index().reset_index().rename(\n",
        "            columns={'index':'barcode', 'barcode_arrangement':'count'})\n",
        "    bc_counts = bars.simple_bar(\n",
        "        barcode_counts['barcode'], barcode_counts['count'],\n",
        "        title='Number of reads per barcode')\n",
        "    bc_counts = annot.subtitle(\n",
        "        bc_counts,\n",
        "        '>{} reads are recommended for further analysis.'.format(\n",
        "            minimum_reads))\n",
        "    bc_counts.xaxis.major_label_orientation = 3.14 / 4\n",
        "    bc_counts = annot.marker_hline(bc_counts, minimum_reads)\n",
        "    aplanat.show(bc_counts)\n",
        "    report.plot(bc_counts, key='bc-plot')\n",
        "\n",
        "    barcode_counts['sufficient data'] = barcode_counts['count'] > minimum_reads\n",
        "    valid_barcodes = set(\n",
        "        barcode_counts.loc[barcode_counts['sufficient data']]['barcode'])\n",
        "    barcodes_found = len(valid_barcodes)\n",
        "    valid_barcodes.discard(\"unclassified\")\n",
        "    valid_barcodes = sorted(valid_barcodes)\n",
        "\n",
        "    def barcode_change(change):\n",
        "        global dataset_name\n",
        "        global dataset_folder\n",
        "        global read_source\n",
        "        global complete_fastq\n",
        "        if change['type'] == 'change' and change['name'] == 'value':\n",
        "            dataset_name = change['new']\n",
        "            dataset_folder = os.path.join(output_folder, dataset_name)\n",
        "            read_source = os.path.join(\n",
        "                output_folder, \"demultiplex\", dataset_name)\n",
        "            complete_fastq = os.path.join(dataset_folder, \"{}.fastq\".format(dataset_name))\n",
        "\n",
        "    barcode_dropdown = widgets.Dropdown(\n",
        "        options=valid_barcodes, value=dataset_name, description='Barcode:')\n",
        "    barcode_dropdown.observe(barcode_change)\n",
        "    print(\"Select a barcode to use for the remainder\")\n",
        "    display(barcode_dropdown)\n",
        "exec_summary.append('Barcodes found', str(barcodes_found), 'balance-scale')"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "application/javascript": [
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              "(function(root) {\n",
              "  function now() {\n",
              "    return new Date();\n",
              "  }\n",
              "\n",
              "  var force = true;\n",
              "\n",
              "  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n",
              "    root._bokeh_onload_callbacks = [];\n",
              "    root._bokeh_is_loading = undefined;\n",
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              "\n",
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              "      var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n",
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              "  }\n",
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              "\n",
              "    function append_mime(data, metadata, element) {\n",
              "      // create a DOM node to render to\n",
              "      var toinsert = this.create_output_subarea(\n",
              "        metadata,\n",
              "        CLASS_NAME,\n",
              "        EXEC_MIME_TYPE\n",
              "      );\n",
              "      this.keyboard_manager.register_events(toinsert);\n",
              "      // Render to node\n",
              "      var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n",
              "      render(props, toinsert[toinsert.length - 1]);\n",
              "      element.append(toinsert);\n",
              "      return toinsert\n",
              "    }\n",
              "\n",
              "    /* Handle when an output is cleared or removed */\n",
              "    events.on('clear_output.CodeCell', handleClearOutput);\n",
              "    events.on('delete.Cell', handleClearOutput);\n",
              "\n",
              "    /* Handle when a new output is added */\n",
              "    events.on('output_added.OutputArea', handleAddOutput);\n",
              "\n",
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              "     */\n",
              "    OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n",
              "      /* Is output safe? */\n",
              "      safe: true,\n",
              "      /* Index of renderer in `output_area.display_order` */\n",
              "      index: 0\n",
              "    });\n",
              "  }\n",
              "\n",
              "  // register the mime type if in Jupyter Notebook environment and previously unregistered\n",
              "  if (root.Jupyter !== undefined) {\n",
              "    var events = require('base/js/events');\n",
              "    var OutputArea = require('notebook/js/outputarea').OutputArea;\n",
              "\n",
              "    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n",
              "      register_renderer(events, OutputArea);\n",
              "    }\n",
              "  }\n",
              "\n",
              "  \n",
              "  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n",
              "    root._bokeh_timeout = Date.now() + 5000;\n",
              "    root._bokeh_failed_load = false;\n",
              "  }\n",
              "\n",
              "  var NB_LOAD_WARNING = {'data': {'text/html':\n",
              "     \"<div style='background-color: #fdd'>\\n\"+\n",
              "     \"<p>\\n\"+\n",
              "     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
              "     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
              "     \"</p>\\n\"+\n",
              "     \"<ul>\\n\"+\n",
              "     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
              "     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
              "     \"</ul>\\n\"+\n",
              "     \"<code>\\n\"+\n",
              "     \"from bokeh.resources import INLINE\\n\"+\n",
              "     \"output_notebook(resources=INLINE)\\n\"+\n",
              "     \"</code>\\n\"+\n",
              "     \"</div>\"}};\n",
              "\n",
              "  function display_loaded() {\n",
              "    var el = document.getElementById(null);\n",
              "    if (el != null) {\n",
              "      el.textContent = \"BokehJS is loading...\";\n",
              "    }\n",
              "    if (root.Bokeh !== undefined) {\n",
              "      if (el != null) {\n",
              "        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n",
              "      }\n",
              "    } else if (Date.now() < root._bokeh_timeout) {\n",
              "      setTimeout(display_loaded, 100)\n",
              "    }\n",
              "  }\n",
              "\n",
              "\n",
              "  function run_callbacks() {\n",
              "    try {\n",
              "      root._bokeh_onload_callbacks.forEach(function(callback) {\n",
              "        if (callback != null)\n",
              "          callback();\n",
              "      });\n",
              "    } finally {\n",
              "      delete root._bokeh_onload_callbacks\n",
              "    }\n",
              "    console.debug(\"Bokeh: all callbacks have finished\");\n",
              "  }\n",
              "\n",
              "  function load_libs(css_urls, js_urls, callback) {\n",
              "    if (css_urls == null) css_urls = [];\n",
              "    if (js_urls == null) js_urls = [];\n",
              "\n",
              "    root._bokeh_onload_callbacks.push(callback);\n",
              "    if (root._bokeh_is_loading > 0) {\n",
              "      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
              "      return null;\n",
              "    }\n",
              "    if (js_urls == null || js_urls.length === 0) {\n",
              "      run_callbacks();\n",
              "      return null;\n",
              "    }\n",
              "    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
              "    root._bokeh_is_loading = css_urls.length + js_urls.length;\n",
              "\n",
              "    function on_load() {\n",
              "      root._bokeh_is_loading--;\n",
              "      if (root._bokeh_is_loading === 0) {\n",
              "        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n",
              "        run_callbacks()\n",
              "      }\n",
              "    }\n",
              "\n",
              "    function on_error() {\n",
              "      console.error(\"failed to load \" + url);\n",
              "    }\n",
              "\n",
              "    for (var i = 0; i < css_urls.length; i++) {\n",
              "      var url = css_urls[i];\n",
              "      const element = document.createElement(\"link\");\n",
              "      element.onload = on_load;\n",
              "      element.onerror = on_error;\n",
              "      element.rel = \"stylesheet\";\n",
              "      element.type = \"text/css\";\n",
              "      element.href = url;\n",
              "      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n",
              "      document.body.appendChild(element);\n",
              "    }\n",
              "\n",
              "    for (var i = 0; i < js_urls.length; i++) {\n",
              "      var url = js_urls[i];\n",
              "      var element = document.createElement('script');\n",
              "      element.onload = on_load;\n",
              "      element.onerror = on_error;\n",
              "      element.async = false;\n",
              "      element.src = url;\n",
              "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
              "      document.head.appendChild(element);\n",
              "    }\n",
              "  };\n",
              "\n",
              "  function inject_raw_css(css) {\n",
              "    const element = document.createElement(\"style\");\n",
              "    element.appendChild(document.createTextNode(css));\n",
              "    document.body.appendChild(element);\n",
              "  }\n",
              "\n",
              "  \n",
              "  var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-1.4.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-1.4.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-1.4.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-1.4.0.min.js\"];\n",
              "  var css_urls = [];\n",
              "  \n",
              "\n",
              "  var inline_js = [\n",
              "    function(Bokeh) {\n",
              "      Bokeh.set_log_level(\"info\");\n",
              "    },\n",
              "    function(Bokeh) {\n",
              "    \n",
              "    \n",
              "    }\n",
              "  ];\n",
              "\n",
              "  function run_inline_js() {\n",
              "    \n",
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              "\n",
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              "\n",
              "  if (root._bokeh_is_loading === 0) {\n",
              "    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
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analysis.\",\"text_font_style\":\"italic\"},\"id\":\"1039\",\"type\":\"Title\"},{\"attributes\":{\"formatter\":{\"id\":\"1045\",\"type\":\"CategoricalTickFormatter\"},\"major_label_orientation\":0.785,\"ticker\":{\"id\":\"1013\",\"type\":\"CategoricalTicker\"}},\"id\":\"1012\",\"type\":\"CategoricalAxis\"},{\"attributes\":{\"line_width\":{\"value\":1.5},\"location\":150},\"id\":\"1040\",\"type\":\"Span\"},{\"attributes\":{\"callback\":null,\"data\":{\"top\":[563,1597,709,1340,1092],\"x\":[\"barcode01\",\"barcode02\",\"barcode03\",\"barcode04\",\"barcode05\"]},\"selected\":{\"id\":\"1047\",\"type\":\"Selection\"},\"selection_policy\":{\"id\":\"1046\",\"type\":\"UnionRenderers\"}},\"id\":\"1034\",\"type\":\"ColumnDataSource\"},{\"attributes\":{},\"id\":\"1013\",\"type\":\"CategoricalTicker\"},{\"attributes\":{\"grid_line_color\":null,\"ticker\":{\"id\":\"1013\",\"type\":\"CategoricalTicker\"}},\"id\":\"1015\",\"type\":\"Grid\"},{\"attributes\":{\"formatter\":{\"id\":\"1043\",\"type\":\"BasicTickFormatter\"},\"ticker\":{\"id\":\"1017\",\"type\":\"BasicTicker\"}},\"id\":\"1016\",\"type\":\"LinearAxis\"},{\"attributes\":{},\"id\":\"1017\",\"type\":\"BasicTicker\"},{\"attributes\":{\"dimension\":1,\"ticker\":{\"id\":\"1017\",\"type\":\"BasicTicker\"}},\"id\":\"1020\",\"type\":\"Grid\"},{\"attributes\":{},\"id\":\"1043\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.1},\"fill_color\":{\"value\":\"#1f77b4\"},\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"#1f77b4\"},\"top\":{\"field\":\"top\"},\"width\":{\"value\":0.9},\"x\":{\"field\":\"x\"}},\"id\":\"1036\",\"type\":\"VBar\"}],\"root_ids\":[\"1001\"]},\"title\":\"Bokeh 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              "        attempts++;\n",
              "        if (attempts > 100) {\n",
              "          clearInterval(timer);\n",
              "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
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              "    }, 10, root)\n",
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            ],
            "application/vnd.bokehjs_exec.v0+json": ""
          },
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              "id": "1001"
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        },
        {
          "output_type": "stream",
          "text": [
            "Select a barcode to use for the remainder\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Dropdown(description='Barcode:', options=('barcode01', 'barcode02', 'barcode03', 'barcode04', 'barcode05'), va…"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "64e8f4fd7e5f470b8f901a8fb18c6f4c"
            }
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "PqUq3LgME-pp",
        "colab_type": "text"
      },
      "source": [
        "\n",
        "Our choice of barcode has been made. Let us quickly review the quality and size distribution of the associated sequences:\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bCOYKyqs7-4a",
        "colab_type": "code",
        "cellView": "form",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 382
        },
        "outputId": "104840a1-b30f-4962-f21b-52158c0333bc"
      },
      "source": [
        "#@markdown **FASTQ assessment** *(click to show)*\n",
        "from aplanat.hist import histogram\n",
        "from bokeh.layouts import gridplot\n",
        "import numpy as np\n",
        "from pysam import FastxFile\n",
        "\n",
        "if read_source is None or complete_fastq is None:\n",
        "    raise RuntimeError(\"Please run the previous code cell.\")\n",
        "\n",
        "!mkdir -p $dataset_folder\n",
        "!rationalise_fastq -i $read_source -o $complete_fastq\n",
        "\n",
        "mean_qualities = list()\n",
        "lengths = list()\n",
        "\n",
        "# open the file and iterate through its records\n",
        "with FastxFile(complete_fastq) as fq:\n",
        "    for rec in fq:\n",
        "        # ONT calculation for \"mean Q score\"\n",
        "        quals = np.fromiter(\n",
        "            (ord(x) - 33 for x in rec.quality),\n",
        "            dtype=int, count=len(rec.quality))\n",
        "        mean_p = np.mean(np.power(10, quals/-10))\n",
        "        mean_qualities.append(-10*np.log10(mean_p))\n",
        "        lengths.append(len(quals))\n",
        "\n",
        "p1 = histogram(\n",
        "    [np.array(mean_qualities)], title=\"Read quality scores\",\n",
        "    x_axis_label=\"quality\", y_axis_label=\"count\",\n",
        "    height=250, width=300)\n",
        "p2 = histogram(\n",
        "    [lengths], title=\"Read lengths\",\n",
        "    x_axis_label=\"read length / bases\", y_axis_label=\"count\",\n",
        "    height=250, width=300, bins=100, xlim=(0, 7000))\n",
        "stats_plots = gridplot((p1, p2), ncols=2)\n",
        "aplanat.show(stats_plots)\n",
        "\n",
        "# Setup report for barcode \n",
        "section = report.add_section(dataset_name)\n",
        "bc_summary = InfoGraphItems()\n",
        "bc_summary.extend((\n",
        "    ('Median read length', str(int(np.median(lengths))), 'align-center', 'b'),\n",
        "    ('Median read quality', str(int(np.median(mean_qualities))), 'thumbs-up', '')))\n",
        "section.markdown(\n",
        "    \"### {} Analysis\".format(dataset_name.capitalize()),\n",
        "    key='{}-heading'.format(dataset_name))\n",
        "section.placeholder('exec-plot')\n",
        "section.plot(stats_plots, key='statsplots')"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Input: /epi2melabs/clone_validation/analysis/demultiplex/barcode02\r\n",
            "Output: /epi2melabs/clone_validation/analysis/barcode02/barcode02.fastq\r\n",
            "Directory detected, concatenating found files.\r\n",
            "Found 1 files.\n",
            "Concatenating files...done.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
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              "\n",
              "(function(root) {\n",
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              "  }\n",
              "\n",
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              "\n",
              "  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n",
              "    root._bokeh_onload_callbacks = [];\n",
              "    root._bokeh_is_loading = undefined;\n",
              "  }\n",
              "\n",
              "  var JS_MIME_TYPE = 'application/javascript';\n",
              "  var HTML_MIME_TYPE = 'text/html';\n",
              "  var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n",
              "  var CLASS_NAME = 'output_bokeh rendered_html';\n",
              "\n",
              "  /**\n",
              "   * Render data to the DOM node\n",
              "   */\n",
              "  function render(props, node) {\n",
              "    var script = document.createElement(\"script\");\n",
              "    node.appendChild(script);\n",
              "  }\n",
              "\n",
              "  /**\n",
              "   * Handle when an output is cleared or removed\n",
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              "  function handleClearOutput(event, handle) {\n",
              "    var cell = handle.cell;\n",
              "\n",
              "    var id = cell.output_area._bokeh_element_id;\n",
              "    var server_id = cell.output_area._bokeh_server_id;\n",
              "    // Clean up Bokeh references\n",
              "    if (id != null && id in Bokeh.index) {\n",
              "      Bokeh.index[id].model.document.clear();\n",
              "      delete Bokeh.index[id];\n",
              "    }\n",
              "\n",
              "    if (server_id !== undefined) {\n",
              "      // Clean up Bokeh references\n",
              "      var cmd = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n",
              "      cell.notebook.kernel.execute(cmd, {\n",
              "        iopub: {\n",
              "          output: function(msg) {\n",
              "            var id = msg.content.text.trim();\n",
              "            if (id in Bokeh.index) {\n",
              "              Bokeh.index[id].model.document.clear();\n",
              "              delete Bokeh.index[id];\n",
              "            }\n",
              "          }\n",
              "        }\n",
              "      });\n",
              "      // Destroy server and session\n",
              "      var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n",
              "      cell.notebook.kernel.execute(cmd);\n",
              "    }\n",
              "  }\n",
              "\n",
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              "  function handleAddOutput(event, handle) {\n",
              "    var output_area = handle.output_area;\n",
              "    var output = handle.output;\n",
              "\n",
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              "    if ((output.output_type != \"display_data\") || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n",
              "      return\n",
              "    }\n",
              "\n",
              "    var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n",
              "\n",
              "    if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n",
              "      toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n",
              "      // store reference to embed id on output_area\n",
              "      output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n",
              "    }\n",
              "    if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n",
              "      var bk_div = document.createElement(\"div\");\n",
              "      bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n",
              "      var script_attrs = bk_div.children[0].attributes;\n",
              "      for (var i = 0; i < script_attrs.length; i++) {\n",
              "        toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n",
              "      }\n",
              "      // store reference to server id on output_area\n",
              "      output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n",
              "    }\n",
              "  }\n",
              "\n",
              "  function register_renderer(events, OutputArea) {\n",
              "\n",
              "    function append_mime(data, metadata, element) {\n",
              "      // create a DOM node to render to\n",
              "      var toinsert = this.create_output_subarea(\n",
              "        metadata,\n",
              "        CLASS_NAME,\n",
              "        EXEC_MIME_TYPE\n",
              "      );\n",
              "      this.keyboard_manager.register_events(toinsert);\n",
              "      // Render to node\n",
              "      var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n",
              "      render(props, toinsert[toinsert.length - 1]);\n",
              "      element.append(toinsert);\n",
              "      return toinsert\n",
              "    }\n",
              "\n",
              "    /* Handle when an output is cleared or removed */\n",
              "    events.on('clear_output.CodeCell', handleClearOutput);\n",
              "    events.on('delete.Cell', handleClearOutput);\n",
              "\n",
              "    /* Handle when a new output is added */\n",
              "    events.on('output_added.OutputArea', handleAddOutput);\n",
              "\n",
              "    /**\n",
              "     * Register the mime type and append_mime function with output_area\n",
              "     */\n",
              "    OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n",
              "      /* Is output safe? */\n",
              "      safe: true,\n",
              "      /* Index of renderer in `output_area.display_order` */\n",
              "      index: 0\n",
              "    });\n",
              "  }\n",
              "\n",
              "  // register the mime type if in Jupyter Notebook environment and previously unregistered\n",
              "  if (root.Jupyter !== undefined) {\n",
              "    var events = require('base/js/events');\n",
              "    var OutputArea = require('notebook/js/outputarea').OutputArea;\n",
              "\n",
              "    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n",
              "      register_renderer(events, OutputArea);\n",
              "    }\n",
              "  }\n",
              "\n",
              "  \n",
              "  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n",
              "    root._bokeh_timeout = Date.now() + 5000;\n",
              "    root._bokeh_failed_load = false;\n",
              "  }\n",
              "\n",
              "  var NB_LOAD_WARNING = {'data': {'text/html':\n",
              "     \"<div style='background-color: #fdd'>\\n\"+\n",
              "     \"<p>\\n\"+\n",
              "     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
              "     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
              "     \"</p>\\n\"+\n",
              "     \"<ul>\\n\"+\n",
              "     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
              "     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
              "     \"</ul>\\n\"+\n",
              "     \"<code>\\n\"+\n",
              "     \"from bokeh.resources import INLINE\\n\"+\n",
              "     \"output_notebook(resources=INLINE)\\n\"+\n",
              "     \"</code>\\n\"+\n",
              "     \"</div>\"}};\n",
              "\n",
              "  function display_loaded() {\n",
              "    var el = document.getElementById(null);\n",
              "    if (el != null) {\n",
              "      el.textContent = \"BokehJS is loading...\";\n",
              "    }\n",
              "    if (root.Bokeh !== undefined) {\n",
              "      if (el != null) {\n",
              "        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n",
              "      }\n",
              "    } else if (Date.now() < root._bokeh_timeout) {\n",
              "      setTimeout(display_loaded, 100)\n",
              "    }\n",
              "  }\n",
              "\n",
              "\n",
              "  function run_callbacks() {\n",
              "    try {\n",
              "      root._bokeh_onload_callbacks.forEach(function(callback) {\n",
              "        if (callback != null)\n",
              "          callback();\n",
              "      });\n",
              "    } finally {\n",
              "      delete root._bokeh_onload_callbacks\n",
              "    }\n",
              "    console.debug(\"Bokeh: all callbacks have finished\");\n",
              "  }\n",
              "\n",
              "  function load_libs(css_urls, js_urls, callback) {\n",
              "    if (css_urls == null) css_urls = [];\n",
              "    if (js_urls == null) js_urls = [];\n",
              "\n",
              "    root._bokeh_onload_callbacks.push(callback);\n",
              "    if (root._bokeh_is_loading > 0) {\n",
              "      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
              "      return null;\n",
              "    }\n",
              "    if (js_urls == null || js_urls.length === 0) {\n",
              "      run_callbacks();\n",
              "      return null;\n",
              "    }\n",
              "    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
              "    root._bokeh_is_loading = css_urls.length + js_urls.length;\n",
              "\n",
              "    function on_load() {\n",
              "      root._bokeh_is_loading--;\n",
              "      if (root._bokeh_is_loading === 0) {\n",
              "        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n",
              "        run_callbacks()\n",
              "      }\n",
              "    }\n",
              "\n",
              "    function on_error() {\n",
              "      console.error(\"failed to load \" + url);\n",
              "    }\n",
              "\n",
              "    for (var i = 0; i < css_urls.length; i++) {\n",
              "      var url = css_urls[i];\n",
              "      const element = document.createElement(\"link\");\n",
              "      element.onload = on_load;\n",
              "      element.onerror = on_error;\n",
              "      element.rel = \"stylesheet\";\n",
              "      element.type = \"text/css\";\n",
              "      element.href = url;\n",
              "      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n",
              "      document.body.appendChild(element);\n",
              "    }\n",
              "\n",
              "    for (var i = 0; i < js_urls.length; i++) {\n",
              "      var url = js_urls[i];\n",
              "      var element = document.createElement('script');\n",
              "      element.onload = on_load;\n",
              "      element.onerror = on_error;\n",
              "      element.async = false;\n",
              "      element.src = url;\n",
              "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
              "      document.head.appendChild(element);\n",
              "    }\n",
              "  };\n",
              "\n",
              "  function inject_raw_css(css) {\n",
              "    const element = document.createElement(\"style\");\n",
              "    element.appendChild(document.createTextNode(css));\n",
              "    document.body.appendChild(element);\n",
              "  }\n",
              "\n",
              "  \n",
              "  var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-1.4.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-1.4.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-1.4.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-1.4.0.min.js\"];\n",
              "  var css_urls = [];\n",
              "  \n",
              "\n",
              "  var inline_js = [\n",
              "    function(Bokeh) {\n",
              "      Bokeh.set_log_level(\"info\");\n",
              "    },\n",
              "    function(Bokeh) {\n",
              "    \n",
              "    \n",
              "    }\n",
              "  ];\n",
              "\n",
              "  function run_inline_js() {\n",
              "    \n",
              "    if (root.Bokeh !== undefined || force === true) {\n",
              "      \n",
              "    for (var i = 0; i < inline_js.length; i++) {\n",
              "      inline_js[i].call(root, root.Bokeh);\n",
              "    }\n",
              "    } else if (Date.now() < root._bokeh_timeout) {\n",
              "      setTimeout(run_inline_js, 100);\n",
              "    } else if (!root._bokeh_failed_load) {\n",
              "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
              "      root._bokeh_failed_load = true;\n",
              "    } else if (force !== true) {\n",
              "      var cell = $(document.getElementById(null)).parents('.cell').data().cell;\n",
              "      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
              "    }\n",
              "\n",
              "  }\n",
              "\n",
              "  if (root._bokeh_is_loading === 0) {\n",
              "    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
              "    run_inline_js();\n",
              "  } else {\n",
              "    load_libs(css_urls, js_urls, function() {\n",
              "      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n",
              "      run_inline_js();\n",
              "    });\n",
              "  }\n",
              "}(window));"
            ],
            "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  var force = true;\n\n  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n    root._bokeh_onload_callbacks = [];\n    root._bokeh_is_loading = undefined;\n  }\n\n  \n\n  \n  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  var NB_LOAD_WARNING = {'data': {'text/html':\n     \"<div style='background-color: #fdd'>\\n\"+\n     \"<p>\\n\"+\n     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n     \"</p>\\n\"+\n     \"<ul>\\n\"+\n     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n     \"</ul>\\n\"+\n     \"<code>\\n\"+\n     \"from bokeh.resources import INLINE\\n\"+\n     \"output_notebook(resources=INLINE)\\n\"+\n     \"</code>\\n\"+\n     \"</div>\"}};\n\n  function display_loaded() {\n    var el = document.getElementById(null);\n    if (el != null) {\n      el.textContent = \"BokehJS is loading...\";\n    }\n    if (root.Bokeh !== undefined) {\n      if (el != null) {\n        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n      }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(display_loaded, 100)\n    }\n  }\n\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) {\n        if (callback != null)\n          callback();\n      });\n    } finally {\n      delete root._bokeh_onload_callbacks\n    }\n    console.debug(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(css_urls, js_urls, callback) {\n    if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n\n    root._bokeh_onload_callbacks.push(callback);\n    if (root._bokeh_is_loading > 0) {\n      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    }\n    if (js_urls == null || js_urls.length === 0) {\n      run_callbacks();\n      return null;\n    }\n    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n    root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n    function on_load() {\n      root._bokeh_is_loading--;\n      if (root._bokeh_is_loading === 0) {\n        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n        run_callbacks()\n      }\n    }\n\n    function on_error() {\n      console.error(\"failed to load \" + url);\n    }\n\n    for (var i = 0; i < css_urls.length; i++) {\n      var url = css_urls[i];\n      const element = document.createElement(\"link\");\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.rel = \"stylesheet\";\n      element.type = \"text/css\";\n      element.href = url;\n      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n      document.body.appendChild(element);\n    }\n\n    for (var i = 0; i < js_urls.length; i++) {\n      var url = js_urls[i];\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n  };\n\n  function inject_raw_css(css) {\n    const element = document.createElement(\"style\");\n    element.appendChild(document.createTextNode(css));\n    document.body.appendChild(element);\n  }\n\n  \n  var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-1.4.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-1.4.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-1.4.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-1.4.0.min.js\"];\n  var css_urls = [];\n  \n\n  var inline_js = [\n    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\n    function(Bokeh) {\n    \n    \n    }\n  ];\n\n  function run_inline_js() {\n    \n    if (root.Bokeh !== undefined || force === true) {\n      \n    for (var i = 0; i < inline_js.length; i++) {\n      inline_js[i].call(root, root.Bokeh);\n    }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    } else if (force !== true) {\n      var cell = $(document.getElementById(null)).parents('.cell').data().cell;\n      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n    }\n\n  }\n\n  if (root._bokeh_is_loading === 0) {\n    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n    run_inline_js();\n  } else {\n    load_libs(css_urls, js_urls, function() {\n      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n      run_inline_js();\n    });\n  }\n}(window));"
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "\n",
              "\n",
              "\n",
              "\n",
              "\n",
              "\n",
              "  <div class=\"bk-root\" id=\"aaa11e76-0685-41bc-8e3f-8a2f9456ee05\" data-root-id=\"1200\"></div>\n"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "application/javascript": [
              "(function(root) {\n",
              "  function embed_document(root) {\n",
              "    \n",
              "  var docs_json = 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length / bases\",\"formatter\":{\"id\":\"1192\",\"type\":\"BasicTickFormatter\"},\"ticker\":{\"id\":\"1150\",\"type\":\"BasicTicker\"}},\"id\":\"1149\",\"type\":\"LinearAxis\"},{\"attributes\":{\"text\":\"Read 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    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-FNVjT-8G_7l",
        "colab_type": "text"
      },
      "source": [
        "## Analysis of a single barcoded analyte\n",
        "\n",
        "In the sections above we have prepared our single-molecule sequence reads for further examination. The remainder of this notebook deals with the assembly of these reads and comparison of the assembly to the reference sequences provided.\n",
        "\n",
        "Use the form below to select a set of parameters for the filtering and downsampling of the sequence collection. The code block will filter the available `.fastq` sequences using `seqkit`, and then further downsample (also using `seqkit`) to produce a dataset of approximately the fold-coverage requested."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kKrCz0RsF2Rg",
        "colab_type": "code",
        "cellView": "form",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 227
        },
        "outputId": "354effac-2020-4bfe-8b70-628c54d99e27"
      },
      "source": [
        "#@markdown **Click the play button** to initialise these values and\n",
        "#@markdown filter the sequence collection.\n",
        "\n",
        "shortest_read = 4000  #@param {type: \"integer\"}\n",
        "longest_read = 5000  #@param {type: \"integer\"}\n",
        "quality_filter =  13#@param {type: \"integer\"}\n",
        "\n",
        "expected_size = 4700 #@param {type: \"integer\"}\n",
        "assemble_x = 150 #@param {type: \"integer\"}\n",
        "\n",
        "#@markdown Select the fastq source data to use subsequently\n",
        "\n",
        "dataset = 'sampled' #@param [\"complete\", \"filtered\", \"sampled\"]\n",
        "\n",
        "print(\"Calculating stats. for complete dataset...\")\n",
        "!seqkit stats --tabular \"$complete_fastq\" > \"$complete_fastq\".stats\n",
        "complete_stats = pd.read_csv(\"{}.stats\".format(complete_fastq), delimiter='\\t')\n",
        "\n",
        "print(\"Filtering dataset by length and quality...\")\n",
        "filtered_fastq = complete_fastq.replace('.fastq', '.filtered.fastq')\n",
        "!seqkit seq --remove-gaps --min-len \"$shortest_read\" --max-len \"$longest_read\" \\\n",
        "    --min-qual \"$quality_filter\" \"$complete_fastq\" > \"$filtered_fastq\"\n",
        "!seqkit stats --tabular \"$filtered_fastq\" > \"$filtered_fastq\".stats\n",
        "filtered_stats = pd.read_csv(\"{}.stats\".format(filtered_fastq), delimiter='\\t')\n",
        "\n",
        "print(\"Subsampling filtered dataset...\")\n",
        "needed_bases = expected_size * assemble_x\n",
        "reqd_reads = int((expected_size * assemble_x) // filtered_stats['avg_len'][0])\n",
        "print(\"Require {} bases ({} total), approximately {} reads\".format(\n",
        "    needed_bases, filtered_stats['sum_len'][0], reqd_reads))\n",
        "\n",
        "sampled_fastq = filtered_fastq.replace(\n",
        "    '.filtered.fastq', '.filtered.sampled.fastq')\n",
        "!seqkit sample --quiet -n \"$reqd_reads\" --two-pass \"$filtered_fastq\" > \"$sampled_fastq\" \n",
        "!seqkit stats --tabular $sampled_fastq > \"$sampled_fastq\".stats\n",
        "sampled_stats = pd.read_csv(\"{}.stats\".format(sampled_fastq), delimiter='\\t')\n",
        "\n",
        "display_stats = pd.concat(\n",
        "    (complete_stats, filtered_stats, sampled_stats)).reset_index(drop=True)\n",
        "display_stats['file'] = display_stats['file'].apply(os.path.basename)\n",
        "display(display_stats)\n",
        "section = report.sections[dataset_name]\n",
        "section.markdown(\n",
        "    \"The table below details read counts and lengths after filtering.\",\n",
        "    key=\"countlead\".format(dataset_name))\n",
        "section.table(display_stats, key='read-stats')\n",
        "\n",
        "fastqs = dict(zip(\n",
        "    ('complete', 'filtered', 'sampled'),\n",
        "    ((complete_fastq, complete_stats),\n",
        "     (filtered_fastq, filtered_stats),\n",
        "     (sampled_fastq, sampled_stats))))\n",
        "fastq_source, stats_source = fastqs[dataset]\n",
        "data_prefix = os.path.splitext(fastq_source)[0]\n",
        "ave_length = int(stats_source['avg_len'][0])\n",
        "print(\"Selecting `{}` for onward use, with average read length {}.\".format(\n",
        "    fastq_source, ave_length))\n",
        "bc_summary.append('Reads used', str(int(stats_source['num_seqs'][0])), 'bookmark')"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Calculating stats. for complete dataset...\n",
            "Filtering dataset by length and quality...\n",
            "Subsampling filtered dataset...\n",
            "Require 705000 bases (2133083 total), approximately 153 reads\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "                               file format type  num_seqs  sum_len  min_len  \\\n",
              "0                   barcode02.fastq  FASTQ  DNA      1597  5064372      135   \n",
              "1          barcode02.filtered.fastq  FASTQ  DNA       465  2133083     4020   \n",
              "2  barcode02.filtered.sampled.fastq  FASTQ  DNA       153   701015     4054   \n",
              "\n",
              "   avg_len  max_len  \n",
              "0   3171.2    20033  \n",
              "1   4587.3     4717  \n",
              "2   4581.8     4717  "
            ],
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>file</th>\n",
              "      <th>format</th>\n",
              "      <th>type</th>\n",
              "      <th>num_seqs</th>\n",
              "      <th>sum_len</th>\n",
              "      <th>min_len</th>\n",
              "      <th>avg_len</th>\n",
              "      <th>max_len</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>barcode02.fastq</td>\n",
              "      <td>FASTQ</td>\n",
              "      <td>DNA</td>\n",
              "      <td>1597</td>\n",
              "      <td>5064372</td>\n",
              "      <td>135</td>\n",
              "      <td>3171.2</td>\n",
              "      <td>20033</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>barcode02.filtered.fastq</td>\n",
              "      <td>FASTQ</td>\n",
              "      <td>DNA</td>\n",
              "      <td>465</td>\n",
              "      <td>2133083</td>\n",
              "      <td>4020</td>\n",
              "      <td>4587.3</td>\n",
              "      <td>4717</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>barcode02.filtered.sampled.fastq</td>\n",
              "      <td>FASTQ</td>\n",
              "      <td>DNA</td>\n",
              "      <td>153</td>\n",
              "      <td>701015</td>\n",
              "      <td>4054</td>\n",
              "      <td>4581.8</td>\n",
              "      <td>4717</td>\n",
              "    </tr>\n",
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              "</div>"
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          },
          "metadata": {
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        {
          "output_type": "stream",
          "text": [
            "Selecting `analysis/barcode02/barcode02.filtered.sampled.fastq` for onward use, with average read length 4581.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "RBfR8XHTQJOK",
        "colab_type": "text"
      },
      "source": [
        "At this point we have selected, filtered, and optionally downsampled our sequencing reads. To check we have a reasonable volume and quality of data to perform the assembly step we will align the reads to the vector reference given at the start of the workflow.\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "S-A0WIoy0gFB",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 323
        },
        "outputId": "7f1b02e0-5881-4f66-db3b-06d103c041a2"
      },
      "source": [
        "# run alignments\n",
        "!rm -f \"$data_prefix\".bam*\n",
        "!mini_align \\\n",
        "    -r \"$target_dna_sequence\" -i \"$fastq_source\" \\\n",
        "    -p \"$data_prefix\" \\\n",
        "    -t 4\n",
        "# calculate read stats\n",
        "!stats_from_bam \"$data_prefix\".bam > \"$data_prefix\".bam.stats\n",
        "# calculate depth\n",
        "!mosdepth -t 2 --flag 1812 \"$data_prefix\".fwd \"$data_prefix\".bam \n",
        "!mosdepth -t 2 --flag 1796 --include-flag 16 \"$data_prefix\".rev \"$data_prefix\".bam"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Constructing minimap index.\r\n",
            "[M::mm_idx_gen::0.003*2.10] collected minimizers\r\n",
            "[M::mm_idx_gen::0.006*2.54] sorted minimizers\r\n",
            "[M::main::0.010*1.96] loaded/built the index for 1 target sequence(s)\r\n",
            "[M::mm_idx_stat] kmer size: 15; skip: 10; is_hpc: 0; #seq: 1\r\n",
            "[M::mm_idx_stat::0.010*1.93] distinct minimizers: 676 (99.85% are singletons); average occurrences: 1.001; average spacing: 5.402\r\n",
            "[M::main] Version: 2.17-r941\r\n",
            "[M::main] CMD: minimap2 -I 16G -x map-ont -d clone_sample_data/vector.fasta.mmi clone_sample_data/vector.fasta\r\n",
            "[M::main] Real time: 0.011 sec; CPU: 0.021 sec; Peak RSS: 0.003 GB\r\n",
            "[M::main::0.006*1.44] loaded/built the index for 1 target sequence(s)\r\n",
            "[M::mm_mapopt_update::0.006*1.43] mid_occ = 3\r\n",
            "[M::mm_idx_stat] kmer size: 15; skip: 10; is_hpc: 0; #seq: 1\r\n",
            "[M::mm_idx_stat::0.006*1.42] distinct minimizers: 676 (99.85% are singletons); average occurrences: 1.001; average spacing: 5.402\n",
            "[M::worker_pipeline::0.077*2.98] mapped 153 sequences\n",
            "[M::main] Version: 2.17-r941\n",
            "[M::main] CMD: minimap2 -x map-ont -t 4 -a -A 2 -B 4 -O 4,24 -E 2,1 clone_sample_data/vector.fasta.mmi analysis/barcode02/barcode02.filtered.sampled.fastq\n",
            "[M::main] Real time: 0.079 sec; CPU: 0.231 sec; Peak RSS: 0.007 GB\n",
            "Mapped/Unmapped/Short/Masked: 152/0/0/0\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "yiOg3Pg7vNVS",
        "colab_type": "text"
      },
      "source": [
        "Two helpful visualizations of these alignment results are the depth of sequencing across the reference and the accuracy of the reads with respect to the reference.\n",
        "\n",
        "> In this experiment we are expecting differences from the reference sequence to occur in our reads, so the accuracy of the reads may appear lower than otherwise expected. The plots also report only a single, primary, alignment of reads: if the read length is a significant fraction of the plasmid size coverage may appear reduced at the edges of the reference and read coverage may be low. This is expected and normal."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "iF48pwDvufOC",
        "colab_type": "code",
        "cellView": "form",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 647
        },
        "outputId": "dea72914-7a7c-4970-c70d-f0368b088dc1"
      },
      "source": [
        "#@markdown **Alignment visualization code** *(click to show)*\n",
        "from aplanat import annot, lines, hist, util\n",
        "from bokeh.layouts import gridplot\n",
        "\n",
        "depth_fwd = pd.read_csv(\n",
        "    '{}.fwd.per-base.bed.gz'.format(data_prefix), sep='\\t',\n",
        "    names=['ref', 'start', 'end', 'depth'])\n",
        "depth_rev = pd.read_csv(\n",
        "    '{}.rev.per-base.bed.gz'.format(data_prefix), sep='\\t',\n",
        "    names=['ref', 'start', 'end', 'depth'])\n",
        "depth_plot = lines.steps(\n",
        "    [depth_fwd['start'], depth_rev['start']],\n",
        "    [depth_fwd['depth'], depth_rev['depth']],\n",
        "    colors=['darkolivegreen', 'maroon'],\n",
        "    names=['Forward', 'Reverse'],\n",
        "    x_axis_label='Position along reference',\n",
        "    y_axis_label='sequencing depth / bases')\n",
        "stats = pd.read_csv(\"{}.bam.stats\".format(data_prefix), sep='\\t')\n",
        "\n",
        "x_grid, pdf = util.kernel_density_estimate(stats['acc'])\n",
        "mode = x_grid[np.argmax(pdf)]\n",
        "acc_plot = lines.line(\n",
        "    [x_grid], [pdf],\n",
        "    x_axis_label=\"read accuracy\", y_axis_label=\"read density\")\n",
        "acc_plot = annot.marker_vline(acc_plot, mode, label='mode: {:.1f}'.format(mode))\n",
        "\n",
        "x_grid, pdf = util.kernel_density_estimate(stats['coverage'])\n",
        "mode = x_grid[np.argmax(pdf)]\n",
        "cover_plot = lines.line(\n",
        "    [x_grid], [pdf],\n",
        "    x_axis_label=\"read coverage\", y_axis_label=\"read density\")\n",
        "cover_plot = annot.marker_vline(cover_plot, mode, label='mode: {:.1f}'.format(mode))\n",
        "\n",
        "plot = gridplot([acc_plot, cover_plot, depth_plot], ncols=2)\n",
        "aplanat.show(plot)\n",
        "section = report.sections[dataset_name]\n",
        "section.markdown(\n",
        "    \"Read metrics with respect to the provided reference are shown below. \"\n",
        "    \"The read coverage is expected to be low for reads of a similar length \"\n",
        "    \"to the reference size. Similarly the coverage graph may show a large \"\n",
        "    \"bias toward the middle of the sequence.\",\n",
        "    key=\"countlead\".format(dataset_name))\n",
        "section.plot(plot, key='read-plots')\n"
      ],
      "execution_count": 11,
      "outputs": [
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Possible fixes:\\n\"+\n     \"</p>\\n\"+\n     \"<ul>\\n\"+\n     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n     \"</ul>\\n\"+\n     \"<code>\\n\"+\n     \"from bokeh.resources import INLINE\\n\"+\n     \"output_notebook(resources=INLINE)\\n\"+\n     \"</code>\\n\"+\n     \"</div>\"}};\n\n  function display_loaded() {\n    var el = document.getElementById(null);\n    if (el != null) {\n      el.textContent = \"BokehJS is loading...\";\n    }\n    if (root.Bokeh !== undefined) {\n      if (el != null) {\n        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n      }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(display_loaded, 100)\n    }\n  }\n\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) {\n        if (callback != null)\n          callback();\n      });\n    } finally {\n      delete root._bokeh_onload_callbacks\n    }\n    console.debug(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(css_urls, js_urls, callback) {\n    if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n\n    root._bokeh_onload_callbacks.push(callback);\n    if (root._bokeh_is_loading > 0) {\n      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    }\n    if (js_urls == null || js_urls.length === 0) {\n      run_callbacks();\n      return null;\n    }\n    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n    root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n    function on_load() {\n      root._bokeh_is_loading--;\n      if (root._bokeh_is_loading === 0) {\n        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n        run_callbacks()\n      }\n    }\n\n    function on_error() {\n      console.error(\"failed to load \" + url);\n    }\n\n    for (var i = 0; i < css_urls.length; i++) {\n      var url = css_urls[i];\n      const element = document.createElement(\"link\");\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.rel = \"stylesheet\";\n      element.type = \"text/css\";\n      element.href = url;\n      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n      document.body.appendChild(element);\n    }\n\n    for (var i = 0; i < js_urls.length; i++) {\n      var url = js_urls[i];\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n  };\n\n  function inject_raw_css(css) {\n    const element = document.createElement(\"style\");\n    element.appendChild(document.createTextNode(css));\n    document.body.appendChild(element);\n  }\n\n  \n  var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-1.4.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-1.4.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-1.4.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-1.4.0.min.js\"];\n  var css_urls = [];\n  \n\n  var inline_js = [\n    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\n    function(Bokeh) {\n    \n    \n    }\n  ];\n\n  function run_inline_js() {\n    \n    if (root.Bokeh !== undefined || force === true) {\n      \n    for (var i = 0; i < inline_js.length; i++) {\n      inline_js[i].call(root, root.Bokeh);\n    }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    } else if (force !== true) {\n      var cell = $(document.getElementById(null)).parents('.cell').data().cell;\n      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n    }\n\n  }\n\n  if (root._bokeh_is_loading === 0) {\n    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n    run_inline_js();\n  } else {\n    load_libs(css_urls, js_urls, function() {\n      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n      run_inline_js();\n    });\n  }\n}(window));"
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      "source": [
        "Provided these plots look reasonable, containing the target coverage across the genome and read accuracy > 93%, we can proceed to the next assembly section of the workflow. If the coverage is low try altering the filtering and sampling settings above."
      ]
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      "cell_type": "markdown",
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      "source": [
        "### De novo assembly of the plasmid sequence\n",
        "\n",
        "It is now time to create an assembly from our selected read data. To do this we will use the `flye` assembler. Flye is a versatile and moderately fast assembler which provides good results in most situations with little parameterisation:"
      ]
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      "cell_type": "code",
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        "colab": {
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          "height": 1000
        },
        "outputId": "1f3a529e-f7fd-4187-ed7e-80bc89325bbd"
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      "source": [
        "#@markdown **Run flye assembly of selected data** *(click to show)*\n",
        "\n",
        "#@markdown The minumum overlap fraction is multiplied by the average read length\n",
        "#@markdown to determine the minimum read overlap size used within the assembly.\n",
        "overlap_fraction = 0.5 #@param {type:\"number\"}\n",
        "\n",
        "assembly_out = os.path.join(dataset_folder, \"flye\")\n",
        "min_overlap = int(overlap_fraction * min(expected_size, ave_length))\n",
        "!rm -rf $assembly_out\n",
        "!mkdir -p \"$assembly_out\"\n",
        "!flye --out-dir $assembly_out --nano-raw $fastq_source \\\n",
        "    --genome-size $expected_size --meta --threads 8 \\\n",
        "    --min-overlap $min_overlap"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[2020-07-30 14:21:51] INFO: Starting Flye 2.7.1-b1590\r\n",
            "[2020-07-30 14:21:51] INFO: >>>STAGE: configure\r\n",
            "[2020-07-30 14:21:51] INFO: Configuring run\r\n",
            "[2020-07-30 14:21:51] INFO: Total read length: 701015\r\n",
            "[2020-07-30 14:21:51] INFO: Input genome size: 4700\r\n",
            "[2020-07-30 14:21:51] INFO: Estimated coverage: 149\r\n",
            "[2020-07-30 14:21:51] INFO: Reads N50/N90: 4608 / 4564\r\n",
            "[2020-07-30 14:21:51] INFO: Selected minimum overlap: 2290\r\n",
            "[2020-07-30 14:21:51] INFO: Selected k-mer size: 15\r\n",
            "[2020-07-30 14:21:51] INFO: >>>STAGE: assembly\r\n",
            "[2020-07-30 14:21:51] INFO: Assembling disjointigs\r\n",
            "[2020-07-30 14:21:51] INFO: Reading sequences\n",
            "[2020-07-30 14:21:51] INFO: Generating solid k-mer index\n",
            "[2020-07-30 14:22:05] INFO: Counting k-mers (1/2):\n",
            "0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% \n",
            "[2020-07-30 14:22:05] INFO: Counting k-mers (2/2):\n",
            "0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% \n",
            "[2020-07-30 14:22:05] INFO: Filling index table (1/2)\n",
            "0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% \n",
            "[2020-07-30 14:22:05] INFO: Filling index table (2/2)\n",
            "0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% \n",
            "[2020-07-30 14:22:10] INFO: Extending reads\n",
            "[2020-07-30 14:22:14] INFO: Overlap-based coverage: 106\n",
            "[2020-07-30 14:22:14] INFO: Median overlap divergence: 0.0885725\n",
            "0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% \n",
            "[2020-07-30 14:22:14] INFO: Assembled 1 disjointigs\n",
            "[2020-07-30 14:22:14] INFO: Generating sequence\n",
            "0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% \n",
            "[2020-07-30 14:22:15] INFO: >>>STAGE: consensus\n",
            "[2020-07-30 14:22:15] INFO: Running Minimap2\n",
            "[2020-07-30 14:22:15] INFO: Computing consensus\n",
            "[2020-07-30 14:22:18] INFO: Alignment error rate: 0.061450\n",
            "[2020-07-30 14:22:18] INFO: >>>STAGE: repeat\n",
            "[2020-07-30 14:22:18] INFO: Building and resolving repeat graph\n",
            "[2020-07-30 14:22:18] INFO: Parsing disjointigs\n",
            "[2020-07-30 14:22:18] INFO: Building repeat graph\n",
            "50% 100% \n",
            "[2020-07-30 14:22:33] INFO: Median overlap divergence: 0.0133364\n",
            "[2020-07-30 14:22:33] INFO: Parsing reads\n",
            "[2020-07-30 14:22:33] INFO: Aligning reads to the graph\n",
            "0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% \n",
            "[2020-07-30 14:22:48] INFO: Aligned read sequence: 678125 / 701015 (0.967347)\n",
            "[2020-07-30 14:22:48] INFO: Median overlap divergence: 0.0267914\n",
            "[2020-07-30 14:22:48] INFO: Mean edge coverage: 24\n",
            "[2020-07-30 14:22:48] INFO: Simplifying the graph\n",
            "[2020-07-30 14:22:48] INFO: >>>STAGE: contigger\n",
            "[2020-07-30 14:22:48] INFO: Generating contigs\n",
            "[2020-07-30 14:22:48] INFO: Reading sequences\n",
            "[2020-07-30 14:22:48] INFO: Generated 1 contigs\n",
            "[2020-07-30 14:22:48] INFO: Added 0 scaffold connections\n",
            "[2020-07-30 14:22:48] INFO: >>>STAGE: polishing\n",
            "[2020-07-30 14:22:48] INFO: Polishing genome (1/1)\n",
            "[2020-07-30 14:22:48] INFO: Running minimap2\n",
            "[2020-07-30 14:22:48] INFO: Separating alignment into bubbles\n",
            "[2020-07-30 14:22:49] INFO: Alignment error rate: 0.038371\n",
            "[2020-07-30 14:22:49] INFO: Correcting bubbles\n",
            "0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% \n",
            "[2020-07-30 14:22:50] INFO: >>>STAGE: finalize\n",
            "[2020-07-30 14:22:50] INFO: Assembly statistics:\n",
            "\n",
            "\tTotal length:\t27238\n",
            "\tFragments:\t1\n",
            "\tFragments N50:\t27238\n",
            "\tLargest frg:\t27238\n",
            "\tScaffolds:\t0\n",
            "\tMean coverage:\t16\n",
            "\n",
            "[2020-07-30 14:22:50] INFO: Final assembly: /epi2melabs/clone_validation/analysis/barcode02/flye/assembly.fasta\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "AcNh7srdV0Qr",
        "colab_type": "text"
      },
      "source": [
        "When `flye` has finished running it will have output something similar to:\n",
        "\n",
        "```\n",
        "\tTotal length:   9997\n",
        "\tFragments:      1\n",
        "\tFragments N50:  9997\n",
        "\tLargest frg:    9997\n",
        "\tScaffolds:      0\n",
        "\tMean coverage:  63\n",
        "```\n",
        "\n",
        "If this is not the case return to the data filtering section above.\n",
        "\n",
        "The statistics above summarise a file output by `flye` which can be inspected by running:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GsgEmnP5SYcl",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 80
        },
        "outputId": "ecbe76dd-19b5-43aa-8b32-0edd63e353c2"
      },
      "source": [
        "assembly = os.path.join(assembly_out, \"assembly.fasta\")\n",
        "flye_info = pd.read_csv(os.path.join(assembly_out, \"assembly_info.txt\"), delimiter='\\t')\n",
        "display(flye_info)\n",
        "section = report.sections[dataset_name]\n",
        "section.markdown('Summary of initial assembly:', key='assm-stats-head')\n",
        "section.table(flye_info, index=False, key='assm-stats')"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "  #seq_name  length  cov. circ. repeat  mult. alt_group  graph_path\n",
              "0  contig_1   27238    16     Y      N      1         *           1"
            ],
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>#seq_name</th>\n",
              "      <th>length</th>\n",
              "      <th>cov.</th>\n",
              "      <th>circ.</th>\n",
              "      <th>repeat</th>\n",
              "      <th>mult.</th>\n",
              "      <th>alt_group</th>\n",
              "      <th>graph_path</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>contig_1</td>\n",
              "      <td>27238</td>\n",
              "      <td>16</td>\n",
              "      <td>Y</td>\n",
              "      <td>N</td>\n",
              "      <td>1</td>\n",
              "      <td>*</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "81z0qyiQa6sw",
        "colab_type": "text"
      },
      "source": [
        "We expect to see a single long contig; the length of this may well be larger than the expected length and similar to whole number multiples of the expected length. If this is so try to run the assembly again with a larger value of the overlap fraction. If you obtain more than a single contig try altering the parameter until only one is obtained.\n",
        "\n",
        "In the table, the contig will likely be identified as circular. A circular contig from the *de novo* assembly of a plasmid will likely contain duplicated sequences at the end of the sequence. Let's check if this is the case by preparing a dotplot showing regions of similarity when the assembly is compared to itself:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "udGy2oxLoZAk",
        "colab_type": "code",
        "cellView": "form",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 417
        },
        "outputId": "a7813d8c-83ab-436c-80b0-a5d77fe1aa98"
      },
      "source": [
        "#@markdown **Creating a dotplot** *(click to show)*\n",
        "import tempfile\n",
        "from aplanat import base\n",
        "assm_dir = os.path.join(output_folder, \"assm_check\")\n",
        "assm2assm = os.path.join(assm_dir, \"aln.paf\")\n",
        "!mkdir -p $assm_dir\n",
        "\n",
        "def last_dot(fasta, ref=None):\n",
        "    tmp = tempfile.mkdtemp()\n",
        "    if ref is None:\n",
        "        ref = fasta\n",
        "    !lastdb $tmp/lastdb $ref\n",
        "    !lastal $tmp/lastdb $fasta > $tmp/alns.maf\n",
        "    records = list()\n",
        "    with open(os.path.join(tmp, \"alns.maf\")) as maf:\n",
        "        while True:\n",
        "            line = maf.readline()\n",
        "            if line.startswith('#'):\n",
        "                continue\n",
        "            elif line.startswith('a'):\n",
        "                r1 = maf.readline().split()[1:5]\n",
        "                r2 = maf.readline().split()[1:5]\n",
        "                blank = maf.readline()\n",
        "                records.append(r1 + r2)\n",
        "            elif line == \"\":\n",
        "                break\n",
        "            else:\n",
        "                print(line)\n",
        "                raise IOError(\"Cannot read alignment file\")\n",
        "    names = ['ref', 'rstart', 'rlen', 'rorient', 'query', 'qstart', 'qlen', 'qorient']\n",
        "    df = pd.DataFrame(records, columns=names)\n",
        "    df = df.loc[df['qorient'] == '+']\n",
        "    for f in ['qstart', 'qlen', 'rstart', 'rlen']:\n",
        "        df[f] = df[f].astype(int)\n",
        "    df['qend'] = df['qstart'] + df['qlen']\n",
        "    df['rend'] = df['rstart'] + df['rlen']\n",
        "    !rm -rf $tmp\n",
        "    return df\n",
        "\n",
        "df = last_dot(assembly)    \n",
        "dotplot = base.simple(\n",
        "    [], [], xlim=(0, max(df['rend'])), ylim=(0, max(df['qend'])),\n",
        "    width=440, height=400, x_axis_label='position', y_axis_label='position')\n",
        "dotplot.segment(df['rstart'], df['qstart'], df['rend'], df['qend'])\n",
        "aplanat.show(dotplot)"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "application/javascript": [
              "\n",
              "(function(root) {\n",
              "  function now() {\n",
              "    return new Date();\n",
              "  }\n",
              "\n",
              "  var force = true;\n",
              "\n",
              "  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n",
              "    root._bokeh_onload_callbacks = [];\n",
              "    root._bokeh_is_loading = undefined;\n",
              "  }\n",
              "\n",
              "  var JS_MIME_TYPE = 'application/javascript';\n",
              "  var HTML_MIME_TYPE = 'text/html';\n",
              "  var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n",
              "  var CLASS_NAME = 'output_bokeh rendered_html';\n",
              "\n",
              "  /**\n",
              "   * Render data to the DOM node\n",
              "   */\n",
              "  function render(props, node) {\n",
              "    var script = document.createElement(\"script\");\n",
              "    node.appendChild(script);\n",
              "  }\n",
              "\n",
              "  /**\n",
              "   * Handle when an output is cleared or removed\n",
              "   */\n",
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              "    var cell = handle.cell;\n",
              "\n",
              "    var id = cell.output_area._bokeh_element_id;\n",
              "    var server_id = cell.output_area._bokeh_server_id;\n",
              "    // Clean up Bokeh references\n",
              "    if (id != null && id in Bokeh.index) {\n",
              "      Bokeh.index[id].model.document.clear();\n",
              "      delete Bokeh.index[id];\n",
              "    }\n",
              "\n",
              "    if (server_id !== undefined) {\n",
              "      // Clean up Bokeh references\n",
              "      var cmd = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n",
              "      cell.notebook.kernel.execute(cmd, {\n",
              "        iopub: {\n",
              "          output: function(msg) {\n",
              "            var id = msg.content.text.trim();\n",
              "            if (id in Bokeh.index) {\n",
              "              Bokeh.index[id].model.document.clear();\n",
              "              delete Bokeh.index[id];\n",
              "            }\n",
              "          }\n",
              "        }\n",
              "      });\n",
              "      // Destroy server and session\n",
              "      var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n",
              "      cell.notebook.kernel.execute(cmd);\n",
              "    }\n",
              "  }\n",
              "\n",
              "  /**\n",
              "   * Handle when a new output is added\n",
              "   */\n",
              "  function handleAddOutput(event, handle) {\n",
              "    var output_area = handle.output_area;\n",
              "    var output = handle.output;\n",
              "\n",
              "    // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n",
              "    if ((output.output_type != \"display_data\") || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n",
              "      return\n",
              "    }\n",
              "\n",
              "    var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n",
              "\n",
              "    if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n",
              "      toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n",
              "      // store reference to embed id on output_area\n",
              "      output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n",
              "    }\n",
              "    if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n",
              "      var bk_div = document.createElement(\"div\");\n",
              "      bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n",
              "      var script_attrs = bk_div.children[0].attributes;\n",
              "      for (var i = 0; i < script_attrs.length; i++) {\n",
              "        toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n",
              "      }\n",
              "      // store reference to server id on output_area\n",
              "      output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n",
              "    }\n",
              "  }\n",
              "\n",
              "  function register_renderer(events, OutputArea) {\n",
              "\n",
              "    function append_mime(data, metadata, element) {\n",
              "      // create a DOM node to render to\n",
              "      var toinsert = this.create_output_subarea(\n",
              "        metadata,\n",
              "        CLASS_NAME,\n",
              "        EXEC_MIME_TYPE\n",
              "      );\n",
              "      this.keyboard_manager.register_events(toinsert);\n",
              "      // Render to node\n",
              "      var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n",
              "      render(props, toinsert[toinsert.length - 1]);\n",
              "      element.append(toinsert);\n",
              "      return toinsert\n",
              "    }\n",
              "\n",
              "    /* Handle when an output is cleared or removed */\n",
              "    events.on('clear_output.CodeCell', handleClearOutput);\n",
              "    events.on('delete.Cell', handleClearOutput);\n",
              "\n",
              "    /* Handle when a new output is added */\n",
              "    events.on('output_added.OutputArea', handleAddOutput);\n",
              "\n",
              "    /**\n",
              "     * Register the mime type and append_mime function with output_area\n",
              "     */\n",
              "    OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n",
              "      /* Is output safe? */\n",
              "      safe: true,\n",
              "      /* Index of renderer in `output_area.display_order` */\n",
              "      index: 0\n",
              "    });\n",
              "  }\n",
              "\n",
              "  // register the mime type if in Jupyter Notebook environment and previously unregistered\n",
              "  if (root.Jupyter !== undefined) {\n",
              "    var events = require('base/js/events');\n",
              "    var OutputArea = require('notebook/js/outputarea').OutputArea;\n",
              "\n",
              "    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n",
              "      register_renderer(events, OutputArea);\n",
              "    }\n",
              "  }\n",
              "\n",
              "  \n",
              "  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n",
              "    root._bokeh_timeout = Date.now() + 5000;\n",
              "    root._bokeh_failed_load = false;\n",
              "  }\n",
              "\n",
              "  var NB_LOAD_WARNING = {'data': {'text/html':\n",
              "     \"<div style='background-color: #fdd'>\\n\"+\n",
              "     \"<p>\\n\"+\n",
              "     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
              "     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
              "     \"</p>\\n\"+\n",
              "     \"<ul>\\n\"+\n",
              "     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
              "     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
              "     \"</ul>\\n\"+\n",
              "     \"<code>\\n\"+\n",
              "     \"from bokeh.resources import INLINE\\n\"+\n",
              "     \"output_notebook(resources=INLINE)\\n\"+\n",
              "     \"</code>\\n\"+\n",
              "     \"</div>\"}};\n",
              "\n",
              "  function display_loaded() {\n",
              "    var el = document.getElementById(null);\n",
              "    if (el != null) {\n",
              "      el.textContent = \"BokehJS is loading...\";\n",
              "    }\n",
              "    if (root.Bokeh !== undefined) {\n",
              "      if (el != null) {\n",
              "        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n",
              "      }\n",
              "    } else if (Date.now() < root._bokeh_timeout) {\n",
              "      setTimeout(display_loaded, 100)\n",
              "    }\n",
              "  }\n",
              "\n",
              "\n",
              "  function run_callbacks() {\n",
              "    try {\n",
              "      root._bokeh_onload_callbacks.forEach(function(callback) {\n",
              "        if (callback != null)\n",
              "          callback();\n",
              "      });\n",
              "    } finally {\n",
              "      delete root._bokeh_onload_callbacks\n",
              "    }\n",
              "    console.debug(\"Bokeh: all callbacks have finished\");\n",
              "  }\n",
              "\n",
              "  function load_libs(css_urls, js_urls, callback) {\n",
              "    if (css_urls == null) css_urls = [];\n",
              "    if (js_urls == null) js_urls = [];\n",
              "\n",
              "    root._bokeh_onload_callbacks.push(callback);\n",
              "    if (root._bokeh_is_loading > 0) {\n",
              "      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
              "      return null;\n",
              "    }\n",
              "    if (js_urls == null || js_urls.length === 0) {\n",
              "      run_callbacks();\n",
              "      return null;\n",
              "    }\n",
              "    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
              "    root._bokeh_is_loading = css_urls.length + js_urls.length;\n",
              "\n",
              "    function on_load() {\n",
              "      root._bokeh_is_loading--;\n",
              "      if (root._bokeh_is_loading === 0) {\n",
              "        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n",
              "        run_callbacks()\n",
              "      }\n",
              "    }\n",
              "\n",
              "    function on_error() {\n",
              "      console.error(\"failed to load \" + url);\n",
              "    }\n",
              "\n",
              "    for (var i = 0; i < css_urls.length; i++) {\n",
              "      var url = css_urls[i];\n",
              "      const element = document.createElement(\"link\");\n",
              "      element.onload = on_load;\n",
              "      element.onerror = on_error;\n",
              "      element.rel = \"stylesheet\";\n",
              "      element.type = \"text/css\";\n",
              "      element.href = url;\n",
              "      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n",
              "      document.body.appendChild(element);\n",
              "    }\n",
              "\n",
              "    for (var i = 0; i < js_urls.length; i++) {\n",
              "      var url = js_urls[i];\n",
              "      var element = document.createElement('script');\n",
              "      element.onload = on_load;\n",
              "      element.onerror = on_error;\n",
              "      element.async = false;\n",
              "      element.src = url;\n",
              "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
              "      document.head.appendChild(element);\n",
              "    }\n",
              "  };\n",
              "\n",
              "  function inject_raw_css(css) {\n",
              "    const element = document.createElement(\"style\");\n",
              "    element.appendChild(document.createTextNode(css));\n",
              "    document.body.appendChild(element);\n",
              "  }\n",
              "\n",
              "  \n",
              "  var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-1.4.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-1.4.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-1.4.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-1.4.0.min.js\"];\n",
              "  var css_urls = [];\n",
              "  \n",
              "\n",
              "  var inline_js = [\n",
              "    function(Bokeh) {\n",
              "      Bokeh.set_log_level(\"info\");\n",
              "    },\n",
              "    function(Bokeh) {\n",
              "    \n",
              "    \n",
              "    }\n",
              "  ];\n",
              "\n",
              "  function run_inline_js() {\n",
              "    \n",
              "    if (root.Bokeh !== undefined || force === true) {\n",
              "      \n",
              "    for (var i = 0; i < inline_js.length; i++) {\n",
              "      inline_js[i].call(root, root.Bokeh);\n",
              "    }\n",
              "    } else if (Date.now() < root._bokeh_timeout) {\n",
              "      setTimeout(run_inline_js, 100);\n",
              "    } else if (!root._bokeh_failed_load) {\n",
              "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
              "      root._bokeh_failed_load = true;\n",
              "    } else if (force !== true) {\n",
              "      var cell = $(document.getElementById(null)).parents('.cell').data().cell;\n",
              "      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
              "    }\n",
              "\n",
              "  }\n",
              "\n",
              "  if (root._bokeh_is_loading === 0) {\n",
              "    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
              "    run_inline_js();\n",
              "  } else {\n",
              "    load_libs(css_urls, js_urls, function() {\n",
              "      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n",
              "      run_inline_js();\n",
              "    });\n",
              "  }\n",
              "}(window));"
            ],
            "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  var force = true;\n\n  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n    root._bokeh_onload_callbacks = [];\n    root._bokeh_is_loading = undefined;\n  }\n\n  \n\n  \n  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  var NB_LOAD_WARNING = {'data': {'text/html':\n     \"<div style='background-color: #fdd'>\\n\"+\n     \"<p>\\n\"+\n     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n     \"may be due to a slow or bad network connection. 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              "\n",
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              "\n",
              "\n",
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              "\n",
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              "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
              "\n",
              "  }\n",
              "  if (root.Bokeh !== undefined) {\n",
              "    embed_document(root);\n",
              "  } else {\n",
              "    var attempts = 0;\n",
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              "        attempts++;\n",
              "        if (attempts > 100) {\n",
              "          clearInterval(timer);\n",
              "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
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              "    }, 10, root)\n",
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              "})(window);"
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            "application/vnd.bokehjs_exec.v0+json": ""
          },
          "metadata": {
            "tags": [],
            "application/vnd.bokehjs_exec.v0+json": {
              "id": "1792"
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    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fzhEFfrNwRUe",
        "colab_type": "text"
      },
      "source": [
        "We would like to obtain a single coherent, linearised sequence repesenting the circular biological molecule. To do this we can break the contig in half and put it back together removing the duplicated sequence. This is done in the following code cell."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Hy6OogsDbf1K",
        "colab_type": "code",
        "cellView": "form",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 542
        },
        "outputId": "a3f971bb-d34d-48e3-9bea-48a79b92c5d2"
      },
      "source": [
        "#@markdown **Circularising assembly by overlap-based trimming** *(click to show)*\n",
        "from aplanat.report import bokeh_table\n",
        "import pysam\n",
        "\n",
        "def split_and_align(sequence_in, name):\n",
        "\n",
        "    print(\"Aligning two halves of assembly...\")\n",
        "    with pysam.FastaFile(sequence_in) as fasta:\n",
        "        if len(fasta.references) > 1:\n",
        "            raise IOError(\"More than one contig found in assembly.\")\n",
        "        rec = fasta.fetch(fasta.references[0])\n",
        "        half = len(rec) // 2\n",
        "        first, second = rec[0:half], rec[half:]\n",
        "        lengths = [len(x) for x in (first, second)]\n",
        "    \n",
        "    split_assm = os.path.join(assm_dir, 'split.{}.fasta')\n",
        "    paf = os.path.join(assm_dir, 'overlap.paf')\n",
        "    for name, seq in enumerate((first, second)):\n",
        "        with open(split_assm.format(name), 'w') as fh:\n",
        "            fh.write(\">seq{}\\n{}\\n\".format(name, seq))\n",
        "    s0, s1 = (split_assm.format(x) for x in range(2))\n",
        "    !minimap2 -cx asm5 $s0 $s1 > $paf 2> /dev/null\n",
        "    return paf, first, second\n",
        "\n",
        "# flye can give lots of repeats, find overlaps and trime iteratively\n",
        "finished = False\n",
        "iteration = 0\n",
        "trimmed_assm = assembly\n",
        "plots = list()\n",
        "while not finished:\n",
        "    iteration += 1\n",
        "    print(\"Iteration: {}\".format(iteration))\n",
        "    print(\" - Trimming sequence according to overlap...\")\n",
        "    paf, first, second = split_and_align(trimmed_assm, 'iter_{}'.format(iteration))\n",
        "    try:\n",
        "        df = pd.read_csv(paf, sep='\\t', header=None)\n",
        "    except ValueError:\n",
        "        print(\" - No alignments found, leaving assembly untrimmed.\")\n",
        "        finished = True\n",
        "    else:\n",
        "        if len(df) != 1:\n",
        "            print(\" - Found multiple alignments, selecting best.\")\n",
        "            df = df[df[2] < 5]\n",
        "            if len(df) == 0:\n",
        "                print(\"- Could not find suitable alignment, leaving assembly untrimmed.\")\n",
        "                finished = True\n",
        "        else:\n",
        "            finished = True\n",
        "        start1, end1 = df[2][0], df[3][0]\n",
        "        start0, end0 = df[7][0], df[8][0]\n",
        "        new_seq = second[:end1] + first[end0:]\n",
        "        trimmed_assm = assembly.replace(\".fasta\", \".trimmed.fasta\")\n",
        "        print(\" - Writing trimmed sequence to {}.\".format(trimmed_assm))\n",
        "        with open(trimmed_assm, 'w') as fh:\n",
        "            fh.write(\">contig_trim\\n{}\\n\".format(new_seq))\n",
        "        print(\"Redoing dotplot...\")\n",
        "        df = last_dot(trimmed_assm)\n",
        "        dotplot = base.simple(\n",
        "            [], [], xlim=(0, max(df['rend'])), ylim=(0, max(df['qend'])),\n",
        "            width=440, height=400, title='After trim iteration {}'.format(iteration),\n",
        "            x_axis_label='position', y_axis_label='position')\n",
        "        dotplot.segment(df['rstart'], df['qstart'], df['rend'], df['qend'])\n",
        "        plots.append(dotplot)\n",
        "        plots.append(bokeh_table(df, index=False))\n",
        "\n",
        "aplanat.show(gridplot(plots, ncols=2))"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Iteration: 1\n",
            " - Trimming sequence according to overlap...\n",
            "Aligning two halves of assembly...\n",
            " - Writing trimmed sequence to analysis/barcode02/flye/assembly.trimmed.fasta.\n",
            "Redoing dotplot...\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
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              "(function(root) {\n",
              "  function now() {\n",
              "    return new Date();\n",
              "  }\n",
              "\n",
              "  var force = true;\n",
              "\n",
              "  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n",
              "    root._bokeh_onload_callbacks = [];\n",
              "    root._bokeh_is_loading = undefined;\n",
              "  }\n",
              "\n",
              "  var JS_MIME_TYPE = 'application/javascript';\n",
              "  var HTML_MIME_TYPE = 'text/html';\n",
              "  var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n",
              "  var CLASS_NAME = 'output_bokeh rendered_html';\n",
              "\n",
              "  /**\n",
              "   * Render data to the DOM node\n",
              "   */\n",
              "  function render(props, node) {\n",
              "    var script = document.createElement(\"script\");\n",
              "    node.appendChild(script);\n",
              "  }\n",
              "\n",
              "  /**\n",
              "   * Handle when an output is cleared or removed\n",
              "   */\n",
              "  function handleClearOutput(event, handle) {\n",
              "    var cell = handle.cell;\n",
              "\n",
              "    var id = cell.output_area._bokeh_element_id;\n",
              "    var server_id = cell.output_area._bokeh_server_id;\n",
              "    // Clean up Bokeh references\n",
              "    if (id != null && id in Bokeh.index) {\n",
              "      Bokeh.index[id].model.document.clear();\n",
              "      delete Bokeh.index[id];\n",
              "    }\n",
              "\n",
              "    if (server_id !== undefined) {\n",
              "      // Clean up Bokeh references\n",
              "      var cmd = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n",
              "      cell.notebook.kernel.execute(cmd, {\n",
              "        iopub: {\n",
              "          output: function(msg) {\n",
              "            var id = msg.content.text.trim();\n",
              "            if (id in Bokeh.index) {\n",
              "              Bokeh.index[id].model.document.clear();\n",
              "              delete Bokeh.index[id];\n",
              "            }\n",
              "          }\n",
              "        }\n",
              "      });\n",
              "      // Destroy server and session\n",
              "      var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n",
              "      cell.notebook.kernel.execute(cmd);\n",
              "    }\n",
              "  }\n",
              "\n",
              "  /**\n",
              "   * Handle when a new output is added\n",
              "   */\n",
              "  function handleAddOutput(event, handle) {\n",
              "    var output_area = handle.output_area;\n",
              "    var output = handle.output;\n",
              "\n",
              "    // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n",
              "    if ((output.output_type != \"display_data\") || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n",
              "      return\n",
              "    }\n",
              "\n",
              "    var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n",
              "\n",
              "    if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n",
              "      toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n",
              "      // store reference to embed id on output_area\n",
              "      output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n",
              "    }\n",
              "    if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n",
              "      var bk_div = document.createElement(\"div\");\n",
              "      bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n",
              "      var script_attrs = bk_div.children[0].attributes;\n",
              "      for (var i = 0; i < script_attrs.length; i++) {\n",
              "        toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n",
              "      }\n",
              "      // store reference to server id on output_area\n",
              "      output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n",
              "    }\n",
              "  }\n",
              "\n",
              "  function register_renderer(events, OutputArea) {\n",
              "\n",
              "    function append_mime(data, metadata, element) {\n",
              "      // create a DOM node to render to\n",
              "      var toinsert = this.create_output_subarea(\n",
              "        metadata,\n",
              "        CLASS_NAME,\n",
              "        EXEC_MIME_TYPE\n",
              "      );\n",
              "      this.keyboard_manager.register_events(toinsert);\n",
              "      // Render to node\n",
              "      var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n",
              "      render(props, toinsert[toinsert.length - 1]);\n",
              "      element.append(toinsert);\n",
              "      return toinsert\n",
              "    }\n",
              "\n",
              "    /* Handle when an output is cleared or removed */\n",
              "    events.on('clear_output.CodeCell', handleClearOutput);\n",
              "    events.on('delete.Cell', handleClearOutput);\n",
              "\n",
              "    /* Handle when a new output is added */\n",
              "    events.on('output_added.OutputArea', handleAddOutput);\n",
              "\n",
              "    /**\n",
              "     * Register the mime type and append_mime function with output_area\n",
              "     */\n",
              "    OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n",
              "      /* Is output safe? */\n",
              "      safe: true,\n",
              "      /* Index of renderer in `output_area.display_order` */\n",
              "      index: 0\n",
              "    });\n",
              "  }\n",
              "\n",
              "  // register the mime type if in Jupyter Notebook environment and previously unregistered\n",
              "  if (root.Jupyter !== undefined) {\n",
              "    var events = require('base/js/events');\n",
              "    var OutputArea = require('notebook/js/outputarea').OutputArea;\n",
              "\n",
              "    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n",
              "      register_renderer(events, OutputArea);\n",
              "    }\n",
              "  }\n",
              "\n",
              "  \n",
              "  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n",
              "    root._bokeh_timeout = Date.now() + 5000;\n",
              "    root._bokeh_failed_load = false;\n",
              "  }\n",
              "\n",
              "  var NB_LOAD_WARNING = {'data': {'text/html':\n",
              "     \"<div style='background-color: #fdd'>\\n\"+\n",
              "     \"<p>\\n\"+\n",
              "     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
              "     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
              "     \"</p>\\n\"+\n",
              "     \"<ul>\\n\"+\n",
              "     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
              "     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
              "     \"</ul>\\n\"+\n",
              "     \"<code>\\n\"+\n",
              "     \"from bokeh.resources import INLINE\\n\"+\n",
              "     \"output_notebook(resources=INLINE)\\n\"+\n",
              "     \"</code>\\n\"+\n",
              "     \"</div>\"}};\n",
              "\n",
              "  function display_loaded() {\n",
              "    var el = document.getElementById(null);\n",
              "    if (el != null) {\n",
              "      el.textContent = \"BokehJS is loading...\";\n",
              "    }\n",
              "    if (root.Bokeh !== undefined) {\n",
              "      if (el != null) {\n",
              "        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n",
              "      }\n",
              "    } else if (Date.now() < root._bokeh_timeout) {\n",
              "      setTimeout(display_loaded, 100)\n",
              "    }\n",
              "  }\n",
              "\n",
              "\n",
              "  function run_callbacks() {\n",
              "    try {\n",
              "      root._bokeh_onload_callbacks.forEach(function(callback) {\n",
              "        if (callback != null)\n",
              "          callback();\n",
              "      });\n",
              "    } finally {\n",
              "      delete root._bokeh_onload_callbacks\n",
              "    }\n",
              "    console.debug(\"Bokeh: all callbacks have finished\");\n",
              "  }\n",
              "\n",
              "  function load_libs(css_urls, js_urls, callback) {\n",
              "    if (css_urls == null) css_urls = [];\n",
              "    if (js_urls == null) js_urls = [];\n",
              "\n",
              "    root._bokeh_onload_callbacks.push(callback);\n",
              "    if (root._bokeh_is_loading > 0) {\n",
              "      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
              "      return null;\n",
              "    }\n",
              "    if (js_urls == null || js_urls.length === 0) {\n",
              "      run_callbacks();\n",
              "      return null;\n",
              "    }\n",
              "    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
              "    root._bokeh_is_loading = css_urls.length + js_urls.length;\n",
              "\n",
              "    function on_load() {\n",
              "      root._bokeh_is_loading--;\n",
              "      if (root._bokeh_is_loading === 0) {\n",
              "        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n",
              "        run_callbacks()\n",
              "      }\n",
              "    }\n",
              "\n",
              "    function on_error() {\n",
              "      console.error(\"failed to load \" + url);\n",
              "    }\n",
              "\n",
              "    for (var i = 0; i < css_urls.length; i++) {\n",
              "      var url = css_urls[i];\n",
              "      const element = document.createElement(\"link\");\n",
              "      element.onload = on_load;\n",
              "      element.onerror = on_error;\n",
              "      element.rel = \"stylesheet\";\n",
              "      element.type = \"text/css\";\n",
              "      element.href = url;\n",
              "      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n",
              "      document.body.appendChild(element);\n",
              "    }\n",
              "\n",
              "    for (var i = 0; i < js_urls.length; i++) {\n",
              "      var url = js_urls[i];\n",
              "      var element = document.createElement('script');\n",
              "      element.onload = on_load;\n",
              "      element.onerror = on_error;\n",
              "      element.async = false;\n",
              "      element.src = url;\n",
              "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
              "      document.head.appendChild(element);\n",
              "    }\n",
              "  };\n",
              "\n",
              "  function inject_raw_css(css) {\n",
              "    const element = document.createElement(\"style\");\n",
              "    element.appendChild(document.createTextNode(css));\n",
              "    document.body.appendChild(element);\n",
              "  }\n",
              "\n",
              "  \n",
              "  var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-1.4.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-1.4.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-1.4.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-1.4.0.min.js\"];\n",
              "  var css_urls = [];\n",
              "  \n",
              "\n",
              "  var inline_js = [\n",
              "    function(Bokeh) {\n",
              "      Bokeh.set_log_level(\"info\");\n",
              "    },\n",
              "    function(Bokeh) {\n",
              "    \n",
              "    \n",
              "    }\n",
              "  ];\n",
              "\n",
              "  function run_inline_js() {\n",
              "    \n",
              "    if (root.Bokeh !== undefined || force === true) {\n",
              "      \n",
              "    for (var i = 0; i < inline_js.length; i++) {\n",
              "      inline_js[i].call(root, root.Bokeh);\n",
              "    }\n",
              "    } else if (Date.now() < root._bokeh_timeout) {\n",
              "      setTimeout(run_inline_js, 100);\n",
              "    } else if (!root._bokeh_failed_load) {\n",
              "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
              "      root._bokeh_failed_load = true;\n",
              "    } else if (force !== true) {\n",
              "      var cell = $(document.getElementById(null)).parents('.cell').data().cell;\n",
              "      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
              "    }\n",
              "\n",
              "  }\n",
              "\n",
              "  if (root._bokeh_is_loading === 0) {\n",
              "    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
              "    run_inline_js();\n",
              "  } else {\n",
              "    load_libs(css_urls, js_urls, function() {\n",
              "      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n",
              "      run_inline_js();\n",
              "    });\n",
              "  }\n",
              "}(window));"
            ],
            "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  var force = true;\n\n  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n    root._bokeh_onload_callbacks = [];\n    root._bokeh_is_loading = undefined;\n  }\n\n  \n\n  \n  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  var NB_LOAD_WARNING = {'data': {'text/html':\n     \"<div style='background-color: #fdd'>\\n\"+\n     \"<p>\\n\"+\n     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n     \"</p>\\n\"+\n     \"<ul>\\n\"+\n     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n     \"</ul>\\n\"+\n     \"<code>\\n\"+\n     \"from bokeh.resources import INLINE\\n\"+\n     \"output_notebook(resources=INLINE)\\n\"+\n     \"</code>\\n\"+\n     \"</div>\"}};\n\n  function display_loaded() {\n    var el = document.getElementById(null);\n    if (el != null) {\n      el.textContent = \"BokehJS is loading...\";\n    }\n    if (root.Bokeh !== undefined) {\n      if (el != null) {\n        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n      }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(display_loaded, 100)\n    }\n  }\n\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) {\n        if (callback != null)\n          callback();\n      });\n    } finally {\n      delete root._bokeh_onload_callbacks\n    }\n    console.debug(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(css_urls, js_urls, callback) {\n    if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n\n    root._bokeh_onload_callbacks.push(callback);\n    if (root._bokeh_is_loading > 0) {\n      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    }\n    if (js_urls == null || js_urls.length === 0) {\n      run_callbacks();\n      return null;\n    }\n    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n    root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n    function on_load() {\n      root._bokeh_is_loading--;\n      if (root._bokeh_is_loading === 0) {\n        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n        run_callbacks()\n      }\n    }\n\n    function on_error() {\n      console.error(\"failed to load \" + url);\n    }\n\n    for (var i = 0; i < css_urls.length; i++) {\n      var url = css_urls[i];\n      const element = document.createElement(\"link\");\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.rel = \"stylesheet\";\n      element.type = \"text/css\";\n      element.href = url;\n      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n      document.body.appendChild(element);\n    }\n\n    for (var i = 0; i < js_urls.length; i++) {\n      var url = js_urls[i];\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n  };\n\n  function inject_raw_css(css) {\n    const element = document.createElement(\"style\");\n    element.appendChild(document.createTextNode(css));\n    document.body.appendChild(element);\n  }\n\n  \n  var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-1.4.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-1.4.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-1.4.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-1.4.0.min.js\"];\n  var css_urls = [];\n  \n\n  var inline_js = [\n    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\n    function(Bokeh) {\n    \n    \n    }\n  ];\n\n  function run_inline_js() {\n    \n    if (root.Bokeh !== undefined || force === true) {\n      \n    for (var i = 0; i < inline_js.length; i++) {\n      inline_js[i].call(root, root.Bokeh);\n    }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    } else if (force !== true) {\n      var cell = $(document.getElementById(null)).parents('.cell').data().cell;\n      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n    }\n\n  }\n\n  if (root._bokeh_is_loading === 0) {\n    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n    run_inline_js();\n  } else {\n    load_libs(css_urls, js_urls, function() {\n      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n      run_inline_js();\n    });\n  }\n}(window));"
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "\n",
              "\n",
              "\n",
              "\n",
              "\n",
              "\n",
              "  <div class=\"bk-root\" id=\"47672414-bb80-4e6e-a873-40310218c482\" data-root-id=\"2382\"></div>\n"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "application/javascript": [
              "(function(root) {\n",
              "  function embed_document(root) {\n",
              "    \n",
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      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "w4YP4vWqLmrz",
        "colab_type": "text"
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      "source": [
        "The result of the above should be a single alignment with no off-diagonal elements. If this is not the case try to amend the assembly parameters. If a single diagonal alignment is not obtainable automatically, it may be possible to examine the alignment co-ordinates and dot plots to manually determine how to edit the sequence."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Y09HcNEjrcs0",
        "colab_type": "code",
        "cellView": "form",
        "colab": {}
      },
      "source": [
        "#@markdown **Manual edit of assembly**\n",
        "from Bio import SeqIO\n",
        "perform_edit = False #@param {type:\"boolean\"}\n",
        "start_position = 0 #@param {type:\"integer\"}\n",
        "end_position =  4539#@param {type:\"integer\"}\n",
        "\n",
        "if perform_edit:\n",
        "    if start_position == end_position:\n",
        "        print(\"Start and end positions should not be equal.\")\n",
        "    else:\n",
        "        fasta = SeqIO.read(trimmed_assm, \"fasta\")\n",
        "        manual_assm = assembly.replace(\".fasta\", \".manualtrim.fasta\")\n",
        "        edited = fasta[start_position:end_position]\n",
        "        SeqIO.write(edited, manual_assm, \"fasta\")\n",
        "        trimmed_assm = manual_assm\n",
        "\n",
        "\n"
      ],
      "execution_count": 18,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fel6-x3KLI_a",
        "colab_type": "text"
      },
      "source": [
        "In this section we have assembled our single-molecule reads into a single contiguous sequence. With a few simple algorithms and manual inspection we have ensured that this contig sequence contains no repetivitive sequence due to the originating target molecule being circular. In the next sections we will improve the quality of the contig and analyse it to determine if it contains the peptide of interest."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3LpEK8wFI51r",
        "colab_type": "text"
      },
      "source": [
        "### Medaka polishing of assembly\n",
        "\n",
        "With our assembly tidied up to remove duplicate sequence, the base-level quality of the assembly can be improved by using medaka:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jvWVxvtkLtXM",
        "colab_type": "code",
        "cellView": "form",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "fd01921c-d620-40ac-b2ae-3421c89d4292"
      },
      "source": [
        "#@markdown **Running medaka to polish assembly** *(click to show)*\n",
        "from Bio import SeqIO\n",
        "medaka_dir = os.path.join(dataset_folder, \"medaka\")\n",
        "medaka_consensus = os.path.join(medaka_dir, \"consensus.fasta\")\n",
        "!rm -rf $medaka_dir\n",
        "!mkdir -p $medaka_dir/\n",
        "!mini_assemble -t $threads -i $fastq_source -r $trimmed_assm -o $medaka_dir/racon/ -p assm 2>/dev/null \n",
        "!run medaka_consensus -i $fastq_source -d $trimmed_assm -o $medaka_dir\n",
        "medaka_seq = SeqIO.read(medaka_consensus, \"fasta\")\n",
        "text = \"The final assembly after medaka correction contains {} bases\".format(len(medaka_seq))\n",
        "bc_summary.append(\"Assembly length\", str(len(medaka_seq)), 'ruler', 'b')\n",
        "print(text)\n",
        "section = report.sections[dataset_name]\n",
        "section.markdown(text, \"medaka-length\")"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Copying FASTX input to workspace: analysis/barcode02/barcode02.filtered.sampled.fastq > analysis/barcode02/medaka/racon//assm.fa.gz\n",
            "Skipped adapter trimming.\n",
            "Skipped pre-assembly correction.\n",
            "Using supplied reference to perform reference-guided consensus.\n",
            "Warning: Parts of this reference might not be polished by racon and such parts will be present in the final consensus unmodified.\n",
            "Running racon read shuffle 1...\n",
            "Running round 1 consensus...\n",
            "Running round 2 consensus...\n",
            "Running round 3 consensus...\n",
            "Running round 4 consensus...\n",
            "Waiting for cleanup.\n",
            "Final assembly written to analysis/barcode02/medaka/racon//assm_final.fa. Have a nice day.\n",
            "Checking program versions\n",
            "This is medaka 1.0.3\n",
            "Program    Version    Required   Pass     \n",
            "bcftools   1.10.2     1.9        True     \n",
            "bgzip      1.10.2     1.9        True     \n",
            "minimap2   2.17       2.11       True     \n",
            "samtools   1.10       1.9        True     \n",
            "tabix      1.10.2     1.9        True     \n",
            "Warning: Output analysis/barcode02/medaka already exists, may use old results.\n",
            "Aligning basecalls to draft\n",
            "Removing previous index file /epi2melabs/clone_validation/analysis/barcode02/flye/assembly.manualtrim.fasta.mmi\n",
            "Removing previous index file /epi2melabs/clone_validation/analysis/barcode02/flye/assembly.manualtrim.fasta.fai\n",
            "Constructing minimap index.\n",
            "[M::mm_idx_gen::0.003*2.02] collected minimizers\n",
            "[M::mm_idx_gen::0.005*2.37] sorted minimizers\n",
            "[M::main::0.009*1.79] loaded/built the index for 1 target sequence(s)\n",
            "[M::mm_idx_stat] kmer size: 15; skip: 10; is_hpc: 0; #seq: 1\n",
            "[M::mm_idx_stat::0.009*1.77] distinct minimizers: 841 (99.88% are singletons); average occurrences: 1.001; average spacing: 5.391\n",
            "[M::main] Version: 2.17-r941\n",
            "[M::main] CMD: minimap2 -I 16G -x map-ont --MD -d /epi2melabs/clone_validation/analysis/barcode02/flye/assembly.manualtrim.fasta.mmi /epi2melabs/clone_validation/analysis/barcode02/flye/assembly.manualtrim.fasta\n",
            "[M::main] Real time: 0.010 sec; CPU: 0.018 sec; Peak RSS: 0.003 GB\n",
            "[M::main::0.006*1.40] loaded/built the index for 1 target sequence(s)\n",
            "[M::mm_mapopt_update::0.006*1.38] mid_occ = 3\n",
            "[M::mm_idx_stat] kmer size: 15; skip: 10; is_hpc: 0; #seq: 1\n",
            "[M::mm_idx_stat::0.006*1.36] distinct minimizers: 841 (99.88% are singletons); average occurrences: 1.001; average spacing: 5.391\n",
            "[M::worker_pipeline::0.224*0.90] mapped 153 sequences\n",
            "[M::main] Version: 2.17-r941\n",
            "[M::main] CMD: minimap2 -x map-ont --MD -t 1 -a -A 2 -B 4 -O 4,24 -E 2,1 /epi2melabs/clone_validation/analysis/barcode02/flye/assembly.manualtrim.fasta.mmi /epi2melabs/clone_validation/analysis/barcode02/barcode02.filtered.sampled.fastq\n",
            "[M::main] Real time: 0.226 sec; CPU: 0.203 sec; Peak RSS: 0.006 GB\n",
            "Running medaka consensus\n",
            "[14:26:58 - Predict] Processing region(s): contig_trim:0-4539\n",
            "[14:26:58 - Predict] Setting tensorflow threads to 1.\n",
            "[14:26:58 - Predict] Processing 1 long region(s) with batching.\n",
            "[14:26:58 - Predict] Using model: /opt/conda/envs/venv_medaka/lib/python3.6/site-packages/medaka/data/r941_min_high_g360_model.hdf5.\n",
            "[14:26:58 - ModelLoad] Building model with cudnn optimization: False\n",
            "[14:26:59 - DLoader] Initializing data loader\n",
            "[14:26:59 - PWorker] Running inference for 0.0M draft bases.\n",
            "[14:26:59 - Sampler] Initializing sampler for consensus of region contig_trim:0-4539.\n",
            "[14:26:59 - Feature] Processed contig_trim:0.0-4538.0 (median depth 108.0)\n",
            "[14:26:59 - Sampler] Took 0.06s to make features.\n",
            "[14:26:59 - Sampler] Region contig_trim:0.0-4538.0 (8068 positions) is smaller than inference chunk length 10000, quarantining.\n",
            "[14:26:59 - PWorker] All done, 1 remainder regions.\n",
            "[14:26:59 - Predict] Processing 1 short region(s).\n",
            "[14:26:59 - ModelLoad] Building model with cudnn optimization: False\n",
            "[14:26:59 - DLoader] Initializing data loader\n",
            "[14:26:59 - PWorker] Running inference for 0.0M draft bases.\n",
            "[14:26:59 - Sampler] Initializing sampler for consensus of region contig_trim:0-4539.\n",
            "[14:26:59 - Feature] Processed contig_trim:0.0-4538.0 (median depth 108.0)\n",
            "[14:26:59 - Sampler] Took 0.06s to make features.\n",
            "[14:27:02 - PWorker] All done, 0 remainder regions.\n",
            "[14:27:02 - Predict] Finished processing all regions.\n",
            "Using medaka stitch to create consensus.\n",
            "[14:27:04 - DataIndex] Loaded 1/1 (100.00%) sample files.\n",
            "[14:27:04 - Stitch] Stitching regions: ['contig_trim:0-']\n",
            "[14:27:04 - DataIndex] Loaded 1/1 (100.00%) sample files.\n",
            "[14:27:04 - Stitch] Processing contig_trim:0-.\n",
            "[14:27:04 - Stitch] Used heuristic 0 times for contig_trim:0-.\n",
            "Polished assembly written to analysis/barcode02/medaka/consensus.fasta, have a nice day.\n",
            "The final assembly after medaka correction contains 4547 bases\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uOjYe_JsIgXo",
        "colab_type": "text"
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      "source": [
        "### Rotating assembly to reference and identifying target peptide\n",
        "\n",
        "In the previous section we first assembled our reads to obtain a single contiguous sequence. This sequence was trimmed to remove duplicated sequence under the assumption that the sequenced molecule is circular. We then improved the base-level quality of the trimmed sequence using `medaka`.\n",
        "\n",
        "In this section we will now compare the assembly to the supplied reference sequences. In order to make this comparison easier we will first attempt to rotate the assembly so that its start co-ordinate matches that of the reference sequence.\n",
        "\n",
        "When the sequence coordinates have been corrected, the BLAST results between the reference and assembled plasmids will be shown. Please assess the sequence alignments for expected coordinates.\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6s6PSqX8gONn",
        "colab_type": "code",
        "cellView": "form",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 638
        },
        "outputId": "3c792ded-93e2-4147-f154-6cbaa1a8bb75"
      },
      "source": [
        "#@markdown **Synchronising assembled plasmid and reference plasmid** *(click to show)*\n",
        "\n",
        "#@markdown Set a tolerance for determining as sequence match lies at the start of the reference:\n",
        "start_tolerance =  20#@param {type:'integer'}\n",
        "\n",
        "from Bio import SearchIO, SeqIO\n",
        "corrected_sequence = medaka_consensus\n",
        "curation_folder = os.path.join(dataset_folder, \"curation\")\n",
        "curated_sequence = os.path.join(curation_folder, \"assembly.fasta\")\n",
        "\n",
        "blast_db = os.path.join(\n",
        "    curation_folder, \"{}.blastdb\".format(os.path.basename(target_dna_sequence)))\n",
        "blast_result = blast_db.replace(\".blastdb\", \"blastxml\")\n",
        "!makeblastdb -in $target_dna_sequence -dbtype nucl -out $blast_db\n",
        "!blastn -db $blast_db -query $medaka_consensus -outfmt 5 -out $blast_result\n",
        "\n",
        "blast_parse = SearchIO.read(blast_result, 'blast-xml')\n",
        "if len(blast_parse) > 0:\n",
        "    qresult = blast_parse[0]\n",
        "    if qresult[0].hit_frame < 0:\n",
        "        print(\"Aligned sequence on the reverse strand - reverse complementing\")\n",
        "        corrected_sequence = os.path.join(medaka_dir, \"consensus_rev_comp.fasta\")\n",
        "        !seqkit seq -p -r -t DNA -v $medaka_consensus > $corrected_sequence\n",
        "        !blastn -db $blast_db -query $corrected_sequence -outfmt 5 -out $blast_result\n",
        "else:\n",
        "    print(\"No blast results\")\n",
        "\n",
        "blast_parse = SearchIO.read(blast_result, 'blast-xml')\n",
        "if len(blast_parse) > 0:\n",
        "    qresult = blast_parse[0]\n",
        "    qres = sorted(qresult, key=lambda x: x.hit_start)\n",
        "    hsp = qres[0]\n",
        "    if hsp.hit_start <= start_tolerance:\n",
        "        cut_pos = hsp.query_start\n",
        "        print(\n",
        "            \"Cutting consensus at {}. Ref. position {}.\".format(\n",
        "                cut_pos, hsp.hit_start))\n",
        "        fasta = SeqIO.read(corrected_sequence, \"fasta\")\n",
        "        # write the new fasta sequence\n",
        "        edited = fasta[cut_pos:] + fasta[:cut_pos]\n",
        "        SeqIO.write(edited, curated_sequence, \"fasta\")\n",
        "    else:\n",
        "        print(\n",
        "            \"Could not find a valid match. The closest match to the \"\n",
        "            \"start was at position {}. The sequence will be left \" \n",
        "            \"unchanged\".format(hsp.hit_start))\n",
        "        curated_sequence = corrected_sequence\n",
        "        !cp $corrected_sequence $curated_sequence\n",
        "else:\n",
        "    curated_sequence = corrected_sequence\n",
        "    !cp $corrected_sequence $curated_sequence\n",
        "\n",
        "print(\"\\nFinal curated sequence: {}.\".format(curated_sequence))\n",
        "print(\"Creating dotplot with rotated assembly against reference...\")\n",
        "df = last_dot(curated_sequence, ref=target_dna_sequence)\n",
        "dotplot = base.simple(\n",
        "    [], [], xlim=(0, max(df['rend'])), ylim=(0, max(df['qend'])),\n",
        "    width=440, height=400, x_axis_label='ref position', y_axis_label='query position')\n",
        "dotplot.segment(df['rstart'], df['qstart'], df['rend'], df['qend'])\n",
        "aplanat.show(dotplot)"
      ],
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "\r\n",
            "\r\n",
            "Building a new DB, current time: 07/30/2020 14:30:06\r\n",
            "New DB name:   /epi2melabs/clone_validation/analysis/barcode02/curation/vector.fasta.blastdb\r\n",
            "New DB title:  clone_sample_data/vector.fasta\r\n",
            "Sequence type: Nucleotide\r\n",
            "Keep MBits: T\r\n",
            "Maximum file size: 1000000000B\r\n",
            "Adding sequences from FASTA; added 1 sequences in 0.000219822 seconds.\r\n",
            "Cutting consensus at 2190. Ref. position 13.\n",
            "\n",
            "Final curated sequence: analysis/barcode02/curation/assembly.fasta.\n",
            "Creating dotplot with rotated assembly against reference...\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
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Possible fixes:\\n\"+\n     \"</p>\\n\"+\n     \"<ul>\\n\"+\n     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n     \"</ul>\\n\"+\n     \"<code>\\n\"+\n     \"from bokeh.resources import INLINE\\n\"+\n     \"output_notebook(resources=INLINE)\\n\"+\n     \"</code>\\n\"+\n     \"</div>\"}};\n\n  function display_loaded() {\n    var el = document.getElementById(null);\n    if (el != null) {\n      el.textContent = \"BokehJS is loading...\";\n    }\n    if (root.Bokeh !== undefined) {\n      if (el != null) {\n        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n      }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(display_loaded, 100)\n    }\n  }\n\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) {\n        if (callback != null)\n          callback();\n      });\n    } finally {\n      delete root._bokeh_onload_callbacks\n    }\n    console.debug(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(css_urls, js_urls, callback) {\n    if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n\n    root._bokeh_onload_callbacks.push(callback);\n    if (root._bokeh_is_loading > 0) {\n      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    }\n    if (js_urls == null || js_urls.length === 0) {\n      run_callbacks();\n      return null;\n    }\n    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n    root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n    function on_load() {\n      root._bokeh_is_loading--;\n      if (root._bokeh_is_loading === 0) {\n        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n        run_callbacks()\n      }\n    }\n\n    function on_error() {\n      console.error(\"failed to load \" + url);\n    }\n\n    for (var i = 0; i < css_urls.length; i++) {\n      var url = css_urls[i];\n      const element = document.createElement(\"link\");\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.rel = \"stylesheet\";\n      element.type = \"text/css\";\n      element.href = url;\n      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n      document.body.appendChild(element);\n    }\n\n    for (var i = 0; i < js_urls.length; i++) {\n      var url = js_urls[i];\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n  };\n\n  function inject_raw_css(css) {\n    const element = document.createElement(\"style\");\n    element.appendChild(document.createTextNode(css));\n    document.body.appendChild(element);\n  }\n\n  \n  var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-1.4.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-1.4.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-1.4.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-1.4.0.min.js\"];\n  var css_urls = [];\n  \n\n  var inline_js = [\n    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\n    function(Bokeh) {\n    \n    \n    }\n  ];\n\n  function run_inline_js() {\n    \n    if (root.Bokeh !== undefined || force === true) {\n      \n    for (var i = 0; i < inline_js.length; i++) {\n      inline_js[i].call(root, root.Bokeh);\n    }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    } else if (force !== true) {\n      var cell = $(document.getElementById(null)).parents('.cell').data().cell;\n      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n    }\n\n  }\n\n  if (root._bokeh_is_loading === 0) {\n    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n    run_inline_js();\n  } else {\n    load_libs(css_urls, js_urls, function() {\n      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n      run_inline_js();\n    });\n  }\n}(window));"
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              "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
              "\n",
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              "    var attempts = 0;\n",
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              "      if (root.Bokeh !== undefined) {\n",
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              "        attempts++;\n",
              "        if (attempts > 100) {\n",
              "          clearInterval(timer);\n",
              "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
              "        }\n",
              "      }\n",
              "    }, 10, root)\n",
              "  }\n",
              "})(window);"
            ],
            "application/vnd.bokehjs_exec.v0+json": ""
          },
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    {
      "cell_type": "markdown",
      "metadata": {
        "id": "FDfAVoSw06Vt",
        "colab_type": "text"
      },
      "source": [
        "As a final sanity check we will align all sequencing reads to our final curated assembly to show the sequencing depth:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tzVofSXk1JuP",
        "colab_type": "code",
        "cellView": "form",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 364
        },
        "outputId": "c355b508-e296-4153-8188-f14f4d1725ed"
      },
      "source": [
        "#@markdown **Alignment of reads to assembly** *(click to show)*\n",
        "\n",
        "eval_path = os.path.join(dataset_folder, 'align_eval')\n",
        "prefix = os.path.join(eval_path, 'reads2assm')\n",
        "!rm -rf $eval_path\n",
        "!mkdir -p $eval_path\n",
        "# double sequence\n",
        "doubled_seq = os.path.join(eval_path, \"doubled.fasta\")\n",
        "seq = SeqIO.read(curated_sequence, \"fasta\")\n",
        "half_len = len(seq) // 2\n",
        "edited = seq[half_len:] + seq + seq[:half_len]\n",
        "SeqIO.write(edited, doubled_seq, \"fasta\")\n",
        "# align\n",
        "print(\"Aligning reads...\", end='')\n",
        "!mini_align \\\n",
        "    -r \"$doubled_seq\" -i \"$complete_fastq\" \\\n",
        "    -p \"$prefix\" \\\n",
        "    -t 4 2> /dev/null\n",
        "print(\"done.\")\n",
        "# calculate read stats\n",
        "!stats_from_bam \"$prefix\".bam > \"$prefix\".bam.stats 2>/dev/null\n",
        "# calculate depth\n",
        "!mosdepth -t 2 --flag 1812 \"$prefix\".fwd \"$prefix\".bam \n",
        "!mosdepth -t 2 --flag 1796 --include-flag 16 \"$prefix\".rev \"$prefix\".bam\n",
        "\n",
        "def unroll_depth(df, size):\n",
        "    hsize = size // 2\n",
        "    start = df['start'] < hsize\n",
        "    mid = (df['start'] >= hsize) & (df['start'] < hsize + size)\n",
        "    end = df['start'] >= size + hsize\n",
        "    for item in ('start', 'end'):\n",
        "        df.loc[start, item] += hsize\n",
        "        df.loc[mid, item] -= hsize\n",
        "        df.loc[end, item] -= size + hsize\n",
        "    result = np.zeros(size, dtype=[('pos', int), ('depth', int)])\n",
        "    result['pos'] = np.arange(size)\n",
        "    for _, row in df.iterrows():\n",
        "        result['depth'][row['start']:row['end']] += row['depth']\n",
        "    return result\n",
        "\n",
        "fwd = pd.read_csv(\n",
        "    '{}.fwd.per-base.bed.gz'.format(prefix), sep='\\t',\n",
        "    names=['ref', 'start', 'end', 'depth'])\n",
        "depth_fwd = unroll_depth(fwd, len(seq))\n",
        "rev = pd.read_csv(\n",
        "    '{}.rev.per-base.bed.gz'.format(prefix), sep='\\t',\n",
        "    names=['ref', 'start', 'end', 'depth'])\n",
        "depth_rev = unroll_depth(rev, len(seq))\n",
        "\n",
        "depth_plot = lines.steps(\n",
        "    [depth_fwd['pos'], depth_rev['pos']],\n",
        "    [depth_fwd['depth'], depth_rev['depth']],\n",
        "    colors=['darkolivegreen', 'maroon'],\n",
        "    names=['Forward', 'Reverse'],\n",
        "    x_axis_label='Position along reference',\n",
        "    y_axis_label='sequencing depth / bases',\n",
        "    title='All reads aligned to circularise assembly')\n",
        "stats = pd.read_csv(\"{}.bam.stats\".format(prefix), sep='\\t')\n",
        "\n",
        "x_grid, pdf = util.kernel_density_estimate(stats['coverage'])\n",
        "mode = x_grid[np.argmax(pdf)]\n",
        "cover_plot = lines.line(\n",
        "    [x_grid], [pdf],\n",
        "    x_axis_label=\"read coverage\", y_axis_label=\"read density\",\n",
        "    title='Alignment read coverage against circularised assembly',\n",
        "    xlim=(90,100))\n",
        "cover_plot = annot.marker_vline(cover_plot, mode, label='mode: {:.1f}'.format(mode))\n",
        "\n",
        "plot = gridplot([cover_plot, depth_plot], ncols=2)\n",
        "aplanat.show(plot)\n",
        "section.plot(plot, key='assm-eval')"
      ],
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Aligning reads...done.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
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              "\n",
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              "\n",
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              "   */\n",
              "  function render(props, node) {\n",
              "    var script = document.createElement(\"script\");\n",
              "    node.appendChild(script);\n",
              "  }\n",
              "\n",
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              "   */\n",
              "  function handleClearOutput(event, handle) {\n",
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              "\n",
              "    var id = cell.output_area._bokeh_element_id;\n",
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              "      delete Bokeh.index[id];\n",
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              "\n",
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              "      var bk_div = document.createElement(\"div\");\n",
              "      bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n",
              "      var script_attrs = bk_div.children[0].attributes;\n",
              "      for (var i = 0; i < script_attrs.length; i++) {\n",
              "        toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n",
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              "\n",
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              "      // create a DOM node to render to\n",
              "      var toinsert = this.create_output_subarea(\n",
              "        metadata,\n",
              "        CLASS_NAME,\n",
              "        EXEC_MIME_TYPE\n",
              "      );\n",
              "      this.keyboard_manager.register_events(toinsert);\n",
              "      // Render to node\n",
              "      var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n",
              "      render(props, toinsert[toinsert.length - 1]);\n",
              "      element.append(toinsert);\n",
              "      return toinsert\n",
              "    }\n",
              "\n",
              "    /* Handle when an output is cleared or removed */\n",
              "    events.on('clear_output.CodeCell', handleClearOutput);\n",
              "    events.on('delete.Cell', handleClearOutput);\n",
              "\n",
              "    /* Handle when a new output is added */\n",
              "    events.on('output_added.OutputArea', handleAddOutput);\n",
              "\n",
              "    /**\n",
              "     * Register the mime type and append_mime function with output_area\n",
              "     */\n",
              "    OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n",
              "      /* Is output safe? */\n",
              "      safe: true,\n",
              "      /* Index of renderer in `output_area.display_order` */\n",
              "      index: 0\n",
              "    });\n",
              "  }\n",
              "\n",
              "  // register the mime type if in Jupyter Notebook environment and previously unregistered\n",
              "  if (root.Jupyter !== undefined) {\n",
              "    var events = require('base/js/events');\n",
              "    var OutputArea = require('notebook/js/outputarea').OutputArea;\n",
              "\n",
              "    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n",
              "      register_renderer(events, OutputArea);\n",
              "    }\n",
              "  }\n",
              "\n",
              "  \n",
              "  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n",
              "    root._bokeh_timeout = Date.now() + 5000;\n",
              "    root._bokeh_failed_load = false;\n",
              "  }\n",
              "\n",
              "  var NB_LOAD_WARNING = {'data': {'text/html':\n",
              "     \"<div style='background-color: #fdd'>\\n\"+\n",
              "     \"<p>\\n\"+\n",
              "     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
              "     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
              "     \"</p>\\n\"+\n",
              "     \"<ul>\\n\"+\n",
              "     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
              "     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
              "     \"</ul>\\n\"+\n",
              "     \"<code>\\n\"+\n",
              "     \"from bokeh.resources import INLINE\\n\"+\n",
              "     \"output_notebook(resources=INLINE)\\n\"+\n",
              "     \"</code>\\n\"+\n",
              "     \"</div>\"}};\n",
              "\n",
              "  function display_loaded() {\n",
              "    var el = document.getElementById(null);\n",
              "    if (el != null) {\n",
              "      el.textContent = \"BokehJS is loading...\";\n",
              "    }\n",
              "    if (root.Bokeh !== undefined) {\n",
              "      if (el != null) {\n",
              "        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n",
              "      }\n",
              "    } else if (Date.now() < root._bokeh_timeout) {\n",
              "      setTimeout(display_loaded, 100)\n",
              "    }\n",
              "  }\n",
              "\n",
              "\n",
              "  function run_callbacks() {\n",
              "    try {\n",
              "      root._bokeh_onload_callbacks.forEach(function(callback) {\n",
              "        if (callback != null)\n",
              "          callback();\n",
              "      });\n",
              "    } finally {\n",
              "      delete root._bokeh_onload_callbacks\n",
              "    }\n",
              "    console.debug(\"Bokeh: all callbacks have finished\");\n",
              "  }\n",
              "\n",
              "  function load_libs(css_urls, js_urls, callback) {\n",
              "    if (css_urls == null) css_urls = [];\n",
              "    if (js_urls == null) js_urls = [];\n",
              "\n",
              "    root._bokeh_onload_callbacks.push(callback);\n",
              "    if (root._bokeh_is_loading > 0) {\n",
              "      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
              "      return null;\n",
              "    }\n",
              "    if (js_urls == null || js_urls.length === 0) {\n",
              "      run_callbacks();\n",
              "      return null;\n",
              "    }\n",
              "    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
              "    root._bokeh_is_loading = css_urls.length + js_urls.length;\n",
              "\n",
              "    function on_load() {\n",
              "      root._bokeh_is_loading--;\n",
              "      if (root._bokeh_is_loading === 0) {\n",
              "        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n",
              "        run_callbacks()\n",
              "      }\n",
              "    }\n",
              "\n",
              "    function on_error() {\n",
              "      console.error(\"failed to load \" + url);\n",
              "    }\n",
              "\n",
              "    for (var i = 0; i < css_urls.length; i++) {\n",
              "      var url = css_urls[i];\n",
              "      const element = document.createElement(\"link\");\n",
              "      element.onload = on_load;\n",
              "      element.onerror = on_error;\n",
              "      element.rel = \"stylesheet\";\n",
              "      element.type = \"text/css\";\n",
              "      element.href = url;\n",
              "      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n",
              "      document.body.appendChild(element);\n",
              "    }\n",
              "\n",
              "    for (var i = 0; i < js_urls.length; i++) {\n",
              "      var url = js_urls[i];\n",
              "      var element = document.createElement('script');\n",
              "      element.onload = on_load;\n",
              "      element.onerror = on_error;\n",
              "      element.async = false;\n",
              "      element.src = url;\n",
              "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
              "      document.head.appendChild(element);\n",
              "    }\n",
              "  };\n",
              "\n",
              "  function inject_raw_css(css) {\n",
              "    const element = document.createElement(\"style\");\n",
              "    element.appendChild(document.createTextNode(css));\n",
              "    document.body.appendChild(element);\n",
              "  }\n",
              "\n",
              "  \n",
              "  var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-1.4.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-1.4.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-1.4.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-1.4.0.min.js\"];\n",
              "  var css_urls = [];\n",
              "  \n",
              "\n",
              "  var inline_js = [\n",
              "    function(Bokeh) {\n",
              "      Bokeh.set_log_level(\"info\");\n",
              "    },\n",
              "    function(Bokeh) {\n",
              "    \n",
              "    \n",
              "    }\n",
              "  ];\n",
              "\n",
              "  function run_inline_js() {\n",
              "    \n",
              "    if (root.Bokeh !== undefined || force === true) {\n",
              "      \n",
              "    for (var i = 0; i < inline_js.length; i++) {\n",
              "      inline_js[i].call(root, root.Bokeh);\n",
              "    }\n",
              "    } else if (Date.now() < root._bokeh_timeout) {\n",
              "      setTimeout(run_inline_js, 100);\n",
              "    } else if (!root._bokeh_failed_load) {\n",
              "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
              "      root._bokeh_failed_load = true;\n",
              "    } else if (force !== true) {\n",
              "      var cell = $(document.getElementById(null)).parents('.cell').data().cell;\n",
              "      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
              "    }\n",
              "\n",
              "  }\n",
              "\n",
              "  if (root._bokeh_is_loading === 0) {\n",
              "    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
              "    run_inline_js();\n",
              "  } else {\n",
              "    load_libs(css_urls, js_urls, function() {\n",
              "      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n",
              "      run_inline_js();\n",
              "    });\n",
              "  }\n",
              "}(window));"
            ],
            "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  var force = true;\n\n  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n    root._bokeh_onload_callbacks = [];\n    root._bokeh_is_loading = undefined;\n  }\n\n  \n\n  \n  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  var NB_LOAD_WARNING = {'data': {'text/html':\n     \"<div style='background-color: #fdd'>\\n\"+\n     \"<p>\\n\"+\n     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n     \"</p>\\n\"+\n     \"<ul>\\n\"+\n     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n     \"</ul>\\n\"+\n     \"<code>\\n\"+\n     \"from bokeh.resources import INLINE\\n\"+\n     \"output_notebook(resources=INLINE)\\n\"+\n     \"</code>\\n\"+\n     \"</div>\"}};\n\n  function display_loaded() {\n    var el = document.getElementById(null);\n    if (el != null) {\n      el.textContent = \"BokehJS is loading...\";\n    }\n    if (root.Bokeh !== undefined) {\n      if (el != null) {\n        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n      }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(display_loaded, 100)\n    }\n  }\n\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) {\n        if (callback != null)\n          callback();\n      });\n    } finally {\n      delete root._bokeh_onload_callbacks\n    }\n    console.debug(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(css_urls, js_urls, callback) {\n    if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n\n    root._bokeh_onload_callbacks.push(callback);\n    if (root._bokeh_is_loading > 0) {\n      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    }\n    if (js_urls == null || js_urls.length === 0) {\n      run_callbacks();\n      return null;\n    }\n    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n    root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n    function on_load() {\n      root._bokeh_is_loading--;\n      if (root._bokeh_is_loading === 0) {\n        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n        run_callbacks()\n      }\n    }\n\n    function on_error() {\n      console.error(\"failed to load \" + url);\n    }\n\n    for (var i = 0; i < css_urls.length; i++) {\n      var url = css_urls[i];\n      const element = document.createElement(\"link\");\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.rel = \"stylesheet\";\n      element.type = \"text/css\";\n      element.href = url;\n      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n      document.body.appendChild(element);\n    }\n\n    for (var i = 0; i < js_urls.length; i++) {\n      var url = js_urls[i];\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n  };\n\n  function inject_raw_css(css) {\n    const element = document.createElement(\"style\");\n    element.appendChild(document.createTextNode(css));\n    document.body.appendChild(element);\n  }\n\n  \n  var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-1.4.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-1.4.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-1.4.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-1.4.0.min.js\"];\n  var css_urls = [];\n  \n\n  var inline_js = [\n    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\n    function(Bokeh) {\n    \n    \n    }\n  ];\n\n  function run_inline_js() {\n    \n    if (root.Bokeh !== undefined || force === true) {\n      \n    for (var i = 0; i < inline_js.length; i++) {\n      inline_js[i].call(root, root.Bokeh);\n    }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    } else if (force !== true) {\n      var cell = $(document.getElementById(null)).parents('.cell').data().cell;\n      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n    }\n\n  }\n\n  if (root._bokeh_is_loading === 0) {\n    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n    run_inline_js();\n  } else {\n    load_libs(css_urls, js_urls, function() {\n      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n      run_inline_js();\n    });\n  }\n}(window));"
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "\n",
              "\n",
              "\n",
              "\n",
              "\n",
              "\n",
              "  <div class=\"bk-root\" id=\"da03190d-11b4-4d6b-9d1a-5708a425a6af\" data-root-id=\"3030\"></div>\n"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "application/javascript": [
              "(function(root) {\n",
              "  function embed_document(root) {\n",
              "    \n",
              "  var docs_json = 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              "  var render_items = [{\"docid\":\"25e8df73-10b1-4dfa-b4df-8001f4be195b\",\"roots\":{\"3030\":\"da03190d-11b4-4d6b-9d1a-5708a425a6af\"}}];\n",
              "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
              "\n",
              "  }\n",
              "  if (root.Bokeh !== undefined) {\n",
              "    embed_document(root);\n",
              "  } else {\n",
              "    var attempts = 0;\n",
              "    var timer = setInterval(function(root) {\n",
              "      if (root.Bokeh !== undefined) {\n",
              "        clearInterval(timer);\n",
              "        embed_document(root);\n",
              "      } else {\n",
              "        attempts++;\n",
              "        if (attempts > 100) {\n",
              "          clearInterval(timer);\n",
              "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
              "        }\n",
              "      }\n",
              "    }, 10, root)\n",
              "  }\n",
              "})(window);"
            ],
            "application/vnd.bokehjs_exec.v0+json": ""
          },
          "metadata": {
            "tags": [],
            "application/vnd.bokehjs_exec.v0+json": {
              "id": "3030"
            }
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "pOi1pl6_YK51",
        "colab_type": "text"
      },
      "source": [
        "The final step of our analysis is to identify the target peptide in our assembly to check that it is present and correct. To do this we will used `diamond` to align the peptide sequence given at the start of the analysis to the translated assembly sequence:\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-O_6vOiqYQC_",
        "colab_type": "code",
        "cellView": "form",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 865
        },
        "outputId": "c9e4df7b-c417-462e-e0d4-193dc016e529"
      },
      "source": [
        "#@markdown **Identifying target peptide in assembly** *(click to show)*\n",
        "from aplanat.graphics import infographic\n",
        "print(\"Assembly: {}\".format(curated_sequence))\n",
        "print(\"Target peptide: {}\".format(target_peptide))\n",
        "!cat $target_peptide\n",
        "\n",
        "diamond_db = os.path.join(medaka_dir, f\"{os.path.basename(target_peptide)}.dmnd\")\n",
        "medaka_diamond = os.path.join(medaka_dir, \"consensus.diamond\")\n",
        "!rm -f $medaka_diamond\n",
        "!diamond makedb --in \"$working_dir\"/\"$target_peptide\" --db \"$diamond_db\" --quiet\n",
        "#!diamond makedb --in garbage.fasta --db \"$diamond_db\" --quiet\n",
        "!diamond blastx --db \"$diamond_db\" -q $curated_sequence \\\n",
        "    --outfmt 0 -o \"$medaka_diamond\" --quiet \\\n",
        "    --threads 1 --more-sensitive --frameshift 15\n",
        "!cat $medaka_diamond\n",
        "peptide_found = True\n",
        "with open(medaka_diamond) as fh:\n",
        "    data = ''.join((\"    {}\".format(x) for x in fh.readlines()))\n",
        "    if \"No hits found\" in data:\n",
        "        peptide_found = False\n",
        "    section = report.sections[dataset_name]\n",
        "    section.markdown(\n",
        "        \"Alignment of target peptide to assembly:\", key=\"pep-align-lead\")\n",
        "    section.markdown(data, key=\"pep-align\")\n",
        "icon = ['times', 'check'][peptide_found]\n",
        "bc_summary.append(\"Peptide found\", \"\", icon)\n",
        "plot = infographic(bc_summary.values())\n",
        "aplanat.show(plot)\n",
        "section = report.sections[dataset_name]\n",
        "section['exec-plot'] = plot\n",
        "\n",
        "# update all barcodes report\n",
        "report['exec-plot'] = infographic(exec_summary.values())\n",
        "fname = os.path.join(output_folder, 'report.html')\n",
        "report.write(fname)\n",
        "print(\"Report written to: {}.\".format(os.path.abspath(fname)))"
      ],
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Assembly: analysis/barcode02/curation/assembly.fasta\n",
            "Target peptide: clone_sample_data/peptide1.fasta\n",
            ">peptide1\r\n",
            "MSAWSHPQFEKGGGSGGGSGGSAWSHPQFEKSGGGGGENLYFQGMSAKAAEGYEQIEVDV\r\n",
            "VAVWKEGYVYENRGSTSVDQKITITKGMKNVNSETRTVTATHSIGSTISTGDAFEIGSVE\r\n",
            "VSYSHSHEESQVSMTETEVYESKVIEHTITIPPTSKFTRWQLNADVGGADIEYMYLIDEV\r\n",
            "TPIGGTQSIPQVITSRAKIIVGRQIILGKTEIRIKHAERKEYMTVVSRKSWPAATLGHSK\r\n",
            "LFKFVLYEDWGGFRIKTLNTMYSGYEYAYSSDQGGIYFDQGTDNPKQRWAINKSLPLRHG\r\n",
            "DVVTFMNKYFTRSGLCYDDGPATNVYCLDKREDKWILEVVG\n",
            "BLASTP 2.3.0+\n",
            "\n",
            "\n",
            "Query= contig_trim_segment0 contig_trim:1.0-4539.0\n",
            "\n",
            "Length=4547\n",
            "\n",
            ">peptide1\n",
            "Length=341\n",
            "\n",
            " Score = 603.6 bits (1555),  Expect = 1.0e-176\n",
            " Identities = 297/297 (100%), Positives = 297/297 (100%), Gaps = 0/297 (0%)\n",
            " Frame = 3\n",
            "\n",
            "Query  3657  MSAKAAEGYEQIEVDVVAVWKEGYVYENRGSTSVDQKITITKGMKNVNSETRTVTATHSI 3836\n",
            "             MSAKAAEGYEQIEVDVVAVWKEGYVYENRGSTSVDQKITITKGMKNVNSETRTVTATHSI\n",
            "Sbjct    45  MSAKAAEGYEQIEVDVVAVWKEGYVYENRGSTSVDQKITITKGMKNVNSETRTVTATHSI 104\n",
            "\n",
            "Query  3837  GSTISTGDAFEIGSVEVSYSHSHEESQVSMTETEVYESKVIEHTITIPPTSKFTRWQLNA 4016\n",
            "             GSTISTGDAFEIGSVEVSYSHSHEESQVSMTETEVYESKVIEHTITIPPTSKFTRWQLNA\n",
            "Sbjct   105  GSTISTGDAFEIGSVEVSYSHSHEESQVSMTETEVYESKVIEHTITIPPTSKFTRWQLNA 164\n",
            "\n",
            "Query  4017  DVGGADIEYMYLIDEVTPIGGTQSIPQVITSRAKIIVGRQIILGKTEIRIKHAERKEYMT 4196\n",
            "             DVGGADIEYMYLIDEVTPIGGTQSIPQVITSRAKIIVGRQIILGKTEIRIKHAERKEYMT\n",
            "Sbjct   165  DVGGADIEYMYLIDEVTPIGGTQSIPQVITSRAKIIVGRQIILGKTEIRIKHAERKEYMT 224\n",
            "\n",
            "Query  4197  VVSRKSWPAATLGHSKLFKFVLYEDWGGFRIKTLNTMYSGYEYAYSSDQGGIYFDQGTDN 4376\n",
            "             VVSRKSWPAATLGHSKLFKFVLYEDWGGFRIKTLNTMYSGYEYAYSSDQGGIYFDQGTDN\n",
            "Sbjct   225  VVSRKSWPAATLGHSKLFKFVLYEDWGGFRIKTLNTMYSGYEYAYSSDQGGIYFDQGTDN 284\n",
            "\n",
            "Query  4377  PKQRWAINKSLPLRHGDVVTFMNKYFTRSGLCYDDGPATNVYCLDKREDKWILEVVG 4547\n",
            "             PKQRWAINKSLPLRHGDVVTFMNKYFTRSGLCYDDGPATNVYCLDKREDKWILEVVG\n",
            "Sbjct   285  PKQRWAINKSLPLRHGDVVTFMNKYFTRSGLCYDDGPATNVYCLDKREDKWILEVVG 341\n",
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/javascript": [
              "\n",
              "(function(root) {\n",
              "  function now() {\n",
              "    return new Date();\n",
              "  }\n",
              "\n",
              "  var force = true;\n",
              "\n",
              "  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n",
              "    root._bokeh_onload_callbacks = [];\n",
              "    root._bokeh_is_loading = undefined;\n",
              "  }\n",
              "\n",
              "  var JS_MIME_TYPE = 'application/javascript';\n",
              "  var HTML_MIME_TYPE = 'text/html';\n",
              "  var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n",
              "  var CLASS_NAME = 'output_bokeh rendered_html';\n",
              "\n",
              "  /**\n",
              "   * Render data to the DOM node\n",
              "   */\n",
              "  function render(props, node) {\n",
              "    var script = document.createElement(\"script\");\n",
              "    node.appendChild(script);\n",
              "  }\n",
              "\n",
              "  /**\n",
              "   * Handle when an output is cleared or removed\n",
              "   */\n",
              "  function handleClearOutput(event, handle) {\n",
              "    var cell = handle.cell;\n",
              "\n",
              "    var id = cell.output_area._bokeh_element_id;\n",
              "    var server_id = cell.output_area._bokeh_server_id;\n",
              "    // Clean up Bokeh references\n",
              "    if (id != null && id in Bokeh.index) {\n",
              "      Bokeh.index[id].model.document.clear();\n",
              "      delete Bokeh.index[id];\n",
              "    }\n",
              "\n",
              "    if (server_id !== undefined) {\n",
              "      // Clean up Bokeh references\n",
              "      var cmd = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n",
              "      cell.notebook.kernel.execute(cmd, {\n",
              "        iopub: {\n",
              "          output: function(msg) {\n",
              "            var id = msg.content.text.trim();\n",
              "            if (id in Bokeh.index) {\n",
              "              Bokeh.index[id].model.document.clear();\n",
              "              delete Bokeh.index[id];\n",
              "            }\n",
              "          }\n",
              "        }\n",
              "      });\n",
              "      // Destroy server and session\n",
              "      var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n",
              "      cell.notebook.kernel.execute(cmd);\n",
              "    }\n",
              "  }\n",
              "\n",
              "  /**\n",
              "   * Handle when a new output is added\n",
              "   */\n",
              "  function handleAddOutput(event, handle) {\n",
              "    var output_area = handle.output_area;\n",
              "    var output = handle.output;\n",
              "\n",
              "    // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n",
              "    if ((output.output_type != \"display_data\") || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n",
              "      return\n",
              "    }\n",
              "\n",
              "    var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n",
              "\n",
              "    if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n",
              "      toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n",
              "      // store reference to embed id on output_area\n",
              "      output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n",
              "    }\n",
              "    if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n",
              "      var bk_div = document.createElement(\"div\");\n",
              "      bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n",
              "      var script_attrs = bk_div.children[0].attributes;\n",
              "      for (var i = 0; i < script_attrs.length; i++) {\n",
              "        toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n",
              "      }\n",
              "      // store reference to server id on output_area\n",
              "      output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n",
              "    }\n",
              "  }\n",
              "\n",
              "  function register_renderer(events, OutputArea) {\n",
              "\n",
              "    function append_mime(data, metadata, element) {\n",
              "      // create a DOM node to render to\n",
              "      var toinsert = this.create_output_subarea(\n",
              "        metadata,\n",
              "        CLASS_NAME,\n",
              "        EXEC_MIME_TYPE\n",
              "      );\n",
              "      this.keyboard_manager.register_events(toinsert);\n",
              "      // Render to node\n",
              "      var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n",
              "      render(props, toinsert[toinsert.length - 1]);\n",
              "      element.append(toinsert);\n",
              "      return toinsert\n",
              "    }\n",
              "\n",
              "    /* Handle when an output is cleared or removed */\n",
              "    events.on('clear_output.CodeCell', handleClearOutput);\n",
              "    events.on('delete.Cell', handleClearOutput);\n",
              "\n",
              "    /* Handle when a new output is added */\n",
              "    events.on('output_added.OutputArea', handleAddOutput);\n",
              "\n",
              "    /**\n",
              "     * Register the mime type and append_mime function with output_area\n",
              "     */\n",
              "    OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n",
              "      /* Is output safe? */\n",
              "      safe: true,\n",
              "      /* Index of renderer in `output_area.display_order` */\n",
              "      index: 0\n",
              "    });\n",
              "  }\n",
              "\n",
              "  // register the mime type if in Jupyter Notebook environment and previously unregistered\n",
              "  if (root.Jupyter !== undefined) {\n",
              "    var events = require('base/js/events');\n",
              "    var OutputArea = require('notebook/js/outputarea').OutputArea;\n",
              "\n",
              "    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n",
              "      register_renderer(events, OutputArea);\n",
              "    }\n",
              "  }\n",
              "\n",
              "  \n",
              "  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n",
              "    root._bokeh_timeout = Date.now() + 5000;\n",
              "    root._bokeh_failed_load = false;\n",
              "  }\n",
              "\n",
              "  var NB_LOAD_WARNING = {'data': {'text/html':\n",
              "     \"<div style='background-color: #fdd'>\\n\"+\n",
              "     \"<p>\\n\"+\n",
              "     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
              "     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
              "     \"</p>\\n\"+\n",
              "     \"<ul>\\n\"+\n",
              "     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
              "     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
              "     \"</ul>\\n\"+\n",
              "     \"<code>\\n\"+\n",
              "     \"from bokeh.resources import INLINE\\n\"+\n",
              "     \"output_notebook(resources=INLINE)\\n\"+\n",
              "     \"</code>\\n\"+\n",
              "     \"</div>\"}};\n",
              "\n",
              "  function display_loaded() {\n",
              "    var el = document.getElementById(null);\n",
              "    if (el != null) {\n",
              "      el.textContent = \"BokehJS is loading...\";\n",
              "    }\n",
              "    if (root.Bokeh !== undefined) {\n",
              "      if (el != null) {\n",
              "        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n",
              "      }\n",
              "    } else if (Date.now() < root._bokeh_timeout) {\n",
              "      setTimeout(display_loaded, 100)\n",
              "    }\n",
              "  }\n",
              "\n",
              "\n",
              "  function run_callbacks() {\n",
              "    try {\n",
              "      root._bokeh_onload_callbacks.forEach(function(callback) {\n",
              "        if (callback != null)\n",
              "          callback();\n",
              "      });\n",
              "    } finally {\n",
              "      delete root._bokeh_onload_callbacks\n",
              "    }\n",
              "    console.debug(\"Bokeh: all callbacks have finished\");\n",
              "  }\n",
              "\n",
              "  function load_libs(css_urls, js_urls, callback) {\n",
              "    if (css_urls == null) css_urls = [];\n",
              "    if (js_urls == null) js_urls = [];\n",
              "\n",
              "    root._bokeh_onload_callbacks.push(callback);\n",
              "    if (root._bokeh_is_loading > 0) {\n",
              "      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
              "      return null;\n",
              "    }\n",
              "    if (js_urls == null || js_urls.length === 0) {\n",
              "      run_callbacks();\n",
              "      return null;\n",
              "    }\n",
              "    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
              "    root._bokeh_is_loading = css_urls.length + js_urls.length;\n",
              "\n",
              "    function on_load() {\n",
              "      root._bokeh_is_loading--;\n",
              "      if (root._bokeh_is_loading === 0) {\n",
              "        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n",
              "        run_callbacks()\n",
              "      }\n",
              "    }\n",
              "\n",
              "    function on_error() {\n",
              "      console.error(\"failed to load \" + url);\n",
              "    }\n",
              "\n",
              "    for (var i = 0; i < css_urls.length; i++) {\n",
              "      var url = css_urls[i];\n",
              "      const element = document.createElement(\"link\");\n",
              "      element.onload = on_load;\n",
              "      element.onerror = on_error;\n",
              "      element.rel = \"stylesheet\";\n",
              "      element.type = \"text/css\";\n",
              "      element.href = url;\n",
              "      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n",
              "      document.body.appendChild(element);\n",
              "    }\n",
              "\n",
              "    for (var i = 0; i < js_urls.length; i++) {\n",
              "      var url = js_urls[i];\n",
              "      var element = document.createElement('script');\n",
              "      element.onload = on_load;\n",
              "      element.onerror = on_error;\n",
              "      element.async = false;\n",
              "      element.src = url;\n",
              "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
              "      document.head.appendChild(element);\n",
              "    }\n",
              "  };\n",
              "\n",
              "  function inject_raw_css(css) {\n",
              "    const element = document.createElement(\"style\");\n",
              "    element.appendChild(document.createTextNode(css));\n",
              "    document.body.appendChild(element);\n",
              "  }\n",
              "\n",
              "  \n",
              "  var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-1.4.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-1.4.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-1.4.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-1.4.0.min.js\"];\n",
              "  var css_urls = [];\n",
              "  \n",
              "\n",
              "  var inline_js = [\n",
              "    function(Bokeh) {\n",
              "      Bokeh.set_log_level(\"info\");\n",
              "    },\n",
              "    function(Bokeh) {\n",
              "    \n",
              "    \n",
              "    }\n",
              "  ];\n",
              "\n",
              "  function run_inline_js() {\n",
              "    \n",
              "    if (root.Bokeh !== undefined || force === true) {\n",
              "      \n",
              "    for (var i = 0; i < inline_js.length; i++) {\n",
              "      inline_js[i].call(root, root.Bokeh);\n",
              "    }\n",
              "    } else if (Date.now() < root._bokeh_timeout) {\n",
              "      setTimeout(run_inline_js, 100);\n",
              "    } else if (!root._bokeh_failed_load) {\n",
              "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
              "      root._bokeh_failed_load = true;\n",
              "    } else if (force !== true) {\n",
              "      var cell = $(document.getElementById(null)).parents('.cell').data().cell;\n",
              "      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
              "    }\n",
              "\n",
              "  }\n",
              "\n",
              "  if (root._bokeh_is_loading === 0) {\n",
              "    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
              "    run_inline_js();\n",
              "  } else {\n",
              "    load_libs(css_urls, js_urls, function() {\n",
              "      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n",
              "      run_inline_js();\n",
              "    });\n",
              "  }\n",
              "}(window));"
            ],
            "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  var force = true;\n\n  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n    root._bokeh_onload_callbacks = [];\n    root._bokeh_is_loading = undefined;\n  }\n\n  \n\n  \n  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  var NB_LOAD_WARNING = {'data': {'text/html':\n     \"<div style='background-color: #fdd'>\\n\"+\n     \"<p>\\n\"+\n     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n     \"</p>\\n\"+\n     \"<ul>\\n\"+\n     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n     \"</ul>\\n\"+\n     \"<code>\\n\"+\n     \"from bokeh.resources import INLINE\\n\"+\n     \"output_notebook(resources=INLINE)\\n\"+\n     \"</code>\\n\"+\n     \"</div>\"}};\n\n  function display_loaded() {\n    var el = document.getElementById(null);\n    if (el != null) {\n      el.textContent = \"BokehJS is loading...\";\n    }\n    if (root.Bokeh !== undefined) {\n      if (el != null) {\n        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n      }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(display_loaded, 100)\n    }\n  }\n\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) {\n        if (callback != null)\n          callback();\n      });\n    } finally {\n      delete root._bokeh_onload_callbacks\n    }\n    console.debug(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(css_urls, js_urls, callback) {\n    if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n\n    root._bokeh_onload_callbacks.push(callback);\n    if (root._bokeh_is_loading > 0) {\n      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    }\n    if (js_urls == null || js_urls.length === 0) {\n      run_callbacks();\n      return null;\n    }\n    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n    root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n    function on_load() {\n      root._bokeh_is_loading--;\n      if (root._bokeh_is_loading === 0) {\n        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n        run_callbacks()\n      }\n    }\n\n    function on_error() {\n      console.error(\"failed to load \" + url);\n    }\n\n    for (var i = 0; i < css_urls.length; i++) {\n      var url = css_urls[i];\n      const element = document.createElement(\"link\");\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.rel = \"stylesheet\";\n      element.type = \"text/css\";\n      element.href = url;\n      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n      document.body.appendChild(element);\n    }\n\n    for (var i = 0; i < js_urls.length; i++) {\n      var url = js_urls[i];\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n  };\n\n  function inject_raw_css(css) {\n    const element = document.createElement(\"style\");\n    element.appendChild(document.createTextNode(css));\n    document.body.appendChild(element);\n  }\n\n  \n  var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-1.4.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-1.4.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-1.4.0.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-1.4.0.min.js\"];\n  var css_urls = [];\n  \n\n  var inline_js = [\n    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\n    function(Bokeh) {\n    \n    \n    }\n  ];\n\n  function run_inline_js() {\n    \n    if (root.Bokeh !== undefined || force === true) {\n      \n    for (var i = 0; i < inline_js.length; i++) {\n      inline_js[i].call(root, root.Bokeh);\n    }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    } else if (force !== true) {\n      var cell = $(document.getElementById(null)).parents('.cell').data().cell;\n      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n    }\n\n  }\n\n  if (root._bokeh_is_loading === 0) {\n    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n    run_inline_js();\n  } else {\n    load_libs(css_urls, js_urls, function() {\n      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n      run_inline_js();\n    });\n  }\n}(window));"
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "\n",
              "\n",
              "\n",
              "\n",
              "\n",
              "\n",
              "  <div class=\"bk-root\" id=\"078841e5-08fc-44de-b53f-1fa13f07d308\" data-root-id=\"3596\"></div>\n"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "application/javascript": [
              "(function(root) {\n",
              "  function embed_document(root) {\n",
              "    \n",
              "  var docs_json = 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        {
          "output_type": "stream",
          "text": [
            "Report written to: /epi2melabs/clone_validation/analysis/report.html.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "dm-LW1TEM_UR",
        "colab_type": "text"
      },
      "source": [
        "If the target peptide has been found in the assembly an alignment of the peptide will be displayed above. This can be inspected for errors.\n",
        "\n",
        "With the analysis complete for this sample we can return to the start of the \"Analysis of a single barcoded analyte\" and analyse another sample."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "iF7WILGOwbI3"
      },
      "source": [
        "## Summary\n",
        "\n",
        "In this workbook we have performed ascertained whether a peptide sequence has been correctly incorporated into a target vector. This was achieved by performing an assembly of the reads, curating this assembly, and finally performing an alignment of the peptide to the assembly sequence.\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kClk-0c3ou7C",
        "colab_type": "text"
      },
      "source": [
        "The analysis presented can be run on any dataset from an Oxford Nanopore Technologies' device. The code will run within **Google Colab** when connected to a local **EPI2ME Labs** notebook server.\n",
        "\n",
        "[Back to EPI2ME Labs](https://colab.research.google.com/github/epi2me-labs/resources/blob/master/welcome.ipynb)"
      ]
    }
  ]
}