Introduction_to_fastq_file.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Introduction to .fastq file",
      "provenance": [],
      "collapsed_sections": [
        "Yu8wQ5mc-69P",
        "vOwokQTOIZ0N",
        "huYtv1u3JDXn",
        "SXx3keHyNPKS",
        "qPBWIDOcVE6L",
        "IXvB3Kpq3MQJ"
      ],
      "toc_visible": true,
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/epi2me-labs/tutorials/blob/master/Introduction_to_fastq_file.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UzUZ_k5x86iT",
        "colab_type": "text"
      },
      "source": [
        "<h1>Fastq</h1>\n",
        "\n",
        "The [fastq format](https://en.wikipedia.org/wiki/FASTQ_format) is (usually) a 4 line string (text) data format denoting a sequence and it's corresponding quality score values.  There different ways of encoding quality in a `.fastq` file however, files from ONT sequencing devices use [sanger phred scores](https://academic.oup.com/nar/article/38/6/1767/3112533). A sequence record is made up of 4 lines:\n",
        "\n",
        "```\n",
        "line 1: Sequence ID and Sequence description\n",
        "line 2: Sequence line e.g. ATCGs\n",
        "line 3: plus symbol (can additionally have description here)\n",
        "line 4: Sequence line qualities\n",
        "```\n",
        "**IMPORTANT:** Line 3 and line 4 must have the same length or the sequence record is not valid.\n",
        "\n",
        "For example a sample record looks like:\n",
        "\n",
        "```\n",
        "@sequence_id sequence_description\n",
        "ATCG\n",
        "+\n",
        "!^%%\n",
        "```\n",
        "The sequence ID must not contain any spaces. Anything after the first space in the sequence ID line will be considered the \"description\".\n",
        "\n",
        "A `.fastq` file may contain multiple records. The default number of records in a fastq file generated during a nanopore run is 4000 reads (16000 lines).\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "cc8B6dK8qvUQ",
        "colab_type": "text"
      },
      "source": [
        "## Useful snippets\n",
        "\n",
        "The following snippets demonstrate common tasks you might want to perform on a single `.fastq` file or a set of such files. For many tasks we recommend the excellent [seqkit](https://github.com/shenwei356/seqkit) program.\n",
        "\n",
        "⚠️ ***Reminder:*** Connect to your locally running EPI2ME Labs Server before running any of the code below. See Run a tutorial on the EPI2ME Labs Server help page for more information."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "iSKV9Kkg0VLa",
        "colab_type": "text"
      },
      "source": [
        "![image.png](data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAdMAAACtCAYAAADroZWoAAAgAElEQVR4Ae29B3QVV5b3y3rre2nem54Zd/d0z6xxj7unw9c9/vzaoZ1o2nGcGQeCiUaYnAwGbIIDYGOMs020CTZgG9uAbXI0GUzOOUtXIEDkHKX91m/fu69Kl3ulKyHBlbSPVqmqTthnn/+pOv/a+5yqWyk3N1cK2yTJUJgcS09SXKF6ubyCkTR8CtsXLCUvtTA5lp5XouAjy1/YvmApeamFybH0vBIFH1n+wvYFS8lLLUyOpeeVKPjI8he2L1hKXmphciw9r0TBR5a/sH3BUvJSC5Nj6XklCj6y/IXtC5aSl1qYHEvPK1HwkeUvbF+wlLzUwuRYel6Jgo8sf2H7gqXkpRYmx9LzShR8ZPkL2xcsJS+1MDmV8rL6kSPgCDgCjoAj4AgUBwEn0+Kg5mUcAUfAEXAEHIEAAk6mATD80BFwBBwBR6CcIJCbK8KWTChK3gTynEwTAOPRjoAj4Ag4AmUUgZyc/Irn5ohcvCi5gY1zIT4YtFySBBwsJyJOpjGA+Kkj4Ag4Ao5AGUUgYInmnj8j5/btkWOzx0t2v66S9VId2dO6qmQ2f1j3nBNPOvnIHw0BOdG4Qg6cTAsByJMdAUfAEXAEygACUSszV06tXyb7B3SXjP/+qaQ/9E+SUe1aCdX8nYSe/qOEav0xvK/5O43X9P/+qeannEjEMo3KS67tTqbJ4eS5HAFHwBFwBFIVgZyLqtn57N1yYPCbkvEEJHqNhNKqSCjtTgk9c6uE6v9FQvVvCWx/CceTnlZF81OO8sjREJGbTLOdTJNByfM4Ao6AI+AIpCYCkfnRs+lbZc9z94dJtMFfJdSwioTq3Zz8Rv4Gf9XyyEGehtj51wQoOJkmAMajHQFHwBFwBFIcgQjRndm5STLrXysZNf4gobTKYeuzKERqebFc0yqrHOSd2bk5DEAShOpkmuLXiqvnCDgCjkCqI8DXgS5evBjdcpIgn8tuU6SO87t3SGajP0nG09dLKO2O5C1RI9B4+7Q7VB5yka+hkDY5mV52j7oAR8ARcAQqLgIQabyQKD5e3iLHRerMOXVc9nZPk4wnr5XQs7h1b0qCTG9JIs9NKg+5yKceDQnaSpqTaZF70Qs4Ao6AI3D5CNi3Xi9f0pWXYLobYR45ckRmzJgh8+fPl+nTp0t6eroqFZuvpDU9NuNbSb/3HyX07F0FEynu2wZ3SKj+rRKqC+FGzlmYFM8y1TgI9S6VTz2FBSfTwhDydEfAEXAEio1AruTkc3/Gs+LixRW7wlIvaARKRbh2CfPmzZNKlSpFt48//lhfMAm6e4PlLk/JMF4XDu+XzKZ3SqjOjQUTIqt46/1FX5NhtW6o9q8lVO1nkv7oNRKqdX2YZJVgEyxWqnOj1kN94RC/v5xML69XvbQj4AiUYQQY4Bnwg5tZU8E4jotOBrn2xmJ+hCKuwhMH9sjeQ8cl/A2e+AN0/oKpc3bmzBnBGrUwdOhQqVKlitSoUUPuvfde6dy5sxw/HnaNnjhxInps+S9rH5m7PDpttGRU/amEGtyemEwh0tp/llC9/5QDn74lJ5fNlrO7Nsnp9Uvk8NjPZE+bhyWj2r9I6JkCZDS4XeuhPg0J5k6dTC+rV72wI+AIVCQEEtBjHAgi5HjxuKxbNEcmT5ooEyZNk9Xb9kUINkdmdf9PeXzANDlF6ZyLkpMTK52fx4wQPT+VabUEfzZTST6SQHzkwaDoxG/CC96b3K9GfiW1a9eWmTNnyrfffiv333+/PPDAA/Lwww/rduutt8qAAQNk4cKF0qVLF3nllVfk3LlzBQtPKjWCQs5F2ff+S2HrkvdE47lqce3Wu1VCta6TYzO/048xnNu9Q04snSunN65QzM9lbpc9HZ+QUK0/hd85jScn7U6th/rop3CI9kZUayfTKBR+4Ag4AhUNgTVr1siQIUOkT58+0W3//v2yYcMGeeedd6Rv374a//nnn8vu3eEX+XMK+zJObo4SX+75/TJ+QBv55V/TpM/gL2XIB53ljj/dLcPnhd9fXPxRTWk5bI6cjQFdh+kgeVp6RK6dBveQaGzIKWCxTGzeZM6xzgnbtm2Tu+66S26++eaoWxcivemmm/T8t7/9rTz00EPyq1/9Ss9vvPFGue6663ROlfImJ5k6L8kT0eFs+mbJbHanhGrflJgEn7ldMp78qRz8/H0Vc3LJLMms98+S8fA1kvHINXLwy75KjqfXLZHMWv8WnkeNR6bMq9a+SeujXg1x8HYyvaS3PMIRcATKKwJmWWElQaDM8/3d3/2dDv533nmn3H777bJr1y6ZO3euxt99991qcdl84KRJkwqFxogtc8U4uee3jWTbmTwrJnvzt1Lp/3xCthw8LcsG1pd2I+fLoZMnJX37VsnYfUAuqHSzQi9IdlaGbNu2Q3bvOyRmE108dUiy9h+QY8dPyO6MdDl0MkxyOedOSGb6dtm+M0OOnI44j0uIUA23s2fPSq9eveQ3v/mNPP744/Loo4/q9uc//1lat26tDx8vv/yy3HLLLfLggw/KY489pum4gLFk9+3bF25hcfWKWIYnVy+SDOY8+cKRWqCx85236EKjzHq/l7M7N8jFowclq8NjkvHUv0uo0X0SevY+Sb/9J3J8wXQl1KzONST09O/DX0mKJVR997SK1ke9GqIWaviU/06meVj4kSPgCFQQBCZPnqxEOmLECF15evToUWFu79QpdboqCpyzHTp0SDZv3iyQBKS6ceNGTTeCiYUs52KYyLYv+EZuvq6x7DydR6a550/KijnzJOvESVkytK081uoFeem11+SFZvVV9sDJGyNW7WGZM/J1ubVyTenSsYn8X//7vTJyzmZNO7lqhPzT738pT6S10jJTd+ZI7sm9MrRTVbmvXltpWe2v8ljHPrJlf5h+i8tbwXZZW1lwNHr0aPnlL38p9913nxImxPn2229H50WxPMeMGaOEisUKqf7rv/6r9O7dW44dO1YgdsE64x5HFjydWDxX0m/7iYQa3ZPYxVvretnd4m+Se+aknFg+X9Lv/0cJNbo3TL7P/k3SH75GDo3sJ3LxnBwaNUAXKIWeuS2+vEb3aH3UqyGiR1BHJ9MgGn7sCDgC5R4BCKFq1arSpk0bOX36tLZ37969MmHCBJkyZYqMHz8+ejxt2rQowYZCIfnJT36i1heFErorzc17NkuGvFpTbnmyk3w9fakcOhmcM8yVJYPqyy8f7iFr0w+rDhtmDpc//ENbycoVObh+gtSv213ST4SJ+cjqkfK/HnxethzPlfPbv5NK/6OKjJy2Vo6dOi0Q9Iw+9aXN4EUSriFHpn3URlp9MDXsQr5kLrZ4XWyESmkeRipXrixY7syTHjx4UIXa6l6w4eHj+uuvF+ZPBw4cGMUxKKfImkRI7NjC2bLrhv9XQo3vjU9+WJNP/0l2t7xPfw3m+KJZkl75HyT07N3h/Gl36qKi/QO7S+7ZU3J0+hhJf+SaxIuZGt+r9VFvpKGXqO5kegkkHuEIOALlGQEGeizMYcOGRV/twK1rrtzYvc2VQrxpaWnyxhtvKDwJyZTUiDmYe/6ozBs9UF7p1FGqV/mfUrPjANmUHZ4lXfDe49J8xAI5HwH79K7F8vxTzWTz2YhFeeGsZO9Nl2070mXr0i+k8oNtZGkoR85v+0p+W/Nl2Xw4bPGePbhLOlz7P+SLxRtkz54MCWXtk+UjX5PKjXpKurJrjuTkGceX1bVGljt37pS//e1vcscdd0jdunV1pbOR5IULYWd1v3795Oc//7n8+te/Vrc5FVv5YitRTDI9sXiWpFeJIVN+Kab/q2q5HuV9VSfTYneLF3QEHIEKiAAk2LRpU3U/2usduHO3bNkiW7dulU2bNqlbl+Pt27dHCWD9+vVKuCxGIhREppdyV45kbV8jIz94Vq6t8aFkn8qRpf1rSbNPZ0vYNhY5vWOhtK/WXLZcEMk9fVgmfdxR/rvpyzJk2Ffy6bvt5Kd3tZUVu3Pl/Nav5fpaXWVtdriWQ3vWSINf/N/SsE0HeeH5DtKhbXvp2K6z9B85TQ4oL9sc7OV1tpElrnDmm5ljxtXLYiRwIlge3ObNmzeX2267TV+Zeemll6ILuCxPsbQpipv36f+U3S3vkdxzZ+T4j7Mk/c6AWzhimR4Y2ltyz52WI1O+Dq8MTvSajbt5i9VdXsgRcATKKQI2kK9cuVKJsW3btvrVHsiAhUd8uYc8vEeJ9UUc86UsPMISY66Q1b4Ek5UfKiOu07J82mD5bHqYZCxP7tk90ubv/zeZH8qWZUObSfOhs/KRaZtHWklGrsjWOX3lXx/uL8cinuHcE0uk6gMtwpbp1q/lT093lXURMj25f4s0+4ebZU76Ua3mwoWLahnnlpQ5GmgruLz33nuKHXOhzIlinUKcYAgm2dnZ0qNHD3XxsqqXfNdee600adJEcKcT4mNnKBWwT3YBEm7e2jdIZpPb5eLRA3Jm6zoJ1f5nCTW8W0INK0tmswcl/b5/lCPjeDDKlewBr0rGU7+IvzLYFyAV0CGe5Ag4AhUSARvE2f/www86nxfr1sVCtQVKwbSGDRsK1inhUsvT4OQjEOEcG374UCr9P41l1e7DcvbcBbl44YxsWzZK/vj3TWTDwdOyfHAjaT1sTpRMz+z8UZ5/qp2EcnNl3bT35ecP9pEjp87L+bMnZP24t+Tn97aVVVlYpt/IHc90kw0HwlrkXjgu33a7Vf7rtYly9EyOSM4F2btzicxeFP6kn7mcTcPi7A03rPFPP/1U/uVf/kVX80KWzJlipWKh1qxZM7ooiXjSH3nkEbVQ27dvH12kZPKKrEtRXo3h04E1fiYnFs/QarL7vyLpN/+9ZFT7DyXSzAa/kLOh7XLx+BHJbFZZQrX+V/yVwf5qTJG7yQs4Ao5ABUHABnOszMWLF+vHBRYsWKB7vtyDBTV33lw958MDy5cvjy6gKci9q/DZO6IXTsiqKR/Lf91cWZ5t01VebFxTfvG7+2XUkpBmm9v936XqgOlRMj21dY7U+dWjsumiSM6RDBnQ5gb5h5urStNn6kuXXm2l0v9RVeZuOSPnN4+Qv7uhqaxWyzS8QOnEga3yYbO/ym8fekZeaddM7nyotUxasj38Ok1JLOcNuLXBrFatWnLNNdfI73//e/m3f/s3JVK+fGSkykccmCvlFZr/+I//0HyrV6/SdheKX4HXYOQxJpmPNrAyt+ZvJevlOnLhyAG5cDhbDn/3qez/4EU58NnbcnZ7+MHo8KiBEqqOVZpgJa9/tKHAHvFER8ARqOAIFGdQT76MuXtFjh3cK7t27pAdO3fJvkMnIqjnyvHs4OcERXLOnJB9WXvl9MUwYVw4dVQy03fIzoy9cjbnrOzbnSXHTp2X3LNHJDNrn5zWdT5mCYtcPHNMMtN3yrYdu2T/EZuJTWxDF6f7rf2zZ8+Wt956S93gq1atkjp16iihQqI2jzp16lR9KBk+fLgu9rIHmOLUm69MxDpN6nOCDe7QDzfs7dVczu7arCt3Lx47KDmnj8uFg1ly6Ov+Eqr1BwnVvTm+Vco7p/45wXzw+4kj4Ag4ApcgwADPCtPgRlxsfE7OxaLP8/Hd33hcpvJjVcmfsaD5zryceYRtH4oISo0XF0y/3OMgOY4aNUq/gFS9enX98AUrnvnAg4VgXosr/j6MQNIfuue7u3yQ4elrZW/PFoIlyhxpZsO/SKj6P4e/fMS8aOzHGuzcP3Rf/K7yko6AI+AIlAwCYWLGomMLkgrHwXNmYjUuUjHHWi6SL5yfREg6j0hNT02PU4+ll8beLNVly5bpoiT7hGAyK55LQp+kf4INFy7WZ/V/11W74V+P+f/Crt2EROo/wVYSfeQyHAFHwBFwBJJEgM8z8lGLPXv26N5+MQaCL5UQkVu0Hwe/Jfy5wAa3RVbtFmCN8iPjz1bRHx33HwcvlR50oY6AI+AIOALJIFBqRGqVR+ZOz+/eIZmN/iQZT18vobQ7ErtrzW2bzD7tDpWHXORriNRn1cfu/QtIsYj4uSPgCDgCjkCRETA3tu2LLKA4BSIEd2bnJsmsf61k1PiDhNIqJ15MVBiR6jullVUO8s7sTPwrMbHqOpnGIuLnjoAj4Ag4AmUHgQihnk3fKnueu1/SH+Ibu3+VUMMqRbNSyd/gr1oeOcjTUIhFakA5mRoSvncEHAFHwBEomwhEvox0Pnu3HBj8prDASEmVn2jjx8P58EL9v4QtVqxP3f4Sjic9rYrmpxzlkaMhzk+tJQLIyTQRMh7vCDgCjoAjUHYQiP5oe66cWr9M9g/orj+rlv7QP0lGtWslVPN3Enr6jxKq9cfwvubvNF7T+ej9gO5aLvp9q6i85CBwMk0OJ8/lCDgCjoAjkOoIBFYP554/I+f27ZFjs8dLdr+ukvVSHdnTuqpkNn9Y95wTTzr5yB8NATnRuEIOnEwLAciTHQFHwBFwBMoYArHznFiZFy9KbmDjXGKtTy1XvNd5nEzL2DXi6joCjoAj4AgkgQDWZbIWZlHyJqjayTQBMB7tCDgCjoAj4Agki4CTabJIeT5HwBFwBBwBRyABAk6mCYDxaEfAEXAEHAFHIFkEnEyTRcrzOQKOgCPgCDgCCRBwMk0AjEc7Ao6AI+AIOALJIuBkmixSns8RcAQcAUfAEUiAgJNpAmA82hFwBBwBR8ARSBYBJ9NkkfJ8joAj4Ag4Ao5AAgScTBMA49GOgCPgCDgCjkCyCDiZJouU53MEHAFHwBFwBBIg4GSaABiPdgQcAUfAEXAEkkXAyTRZpDyfI+AIOAKOgCOQAIFKFy9eFN8cA78G/Brwa8CvAb8Gin8NVAqFQpKVlSV79uzxzTHwa8CvAb8G/Brwa6AY14C7eROY7B7tCDgCjoAj4Agki0Cl3Nxc8c0x8GvArwG/Bvwa8Gug+NeAW6bJPnZ4PkfAEXAEHAFHIAECTqYJgPFoRyBVEcB68OAIOAKphYCTaWr1h2vjCORDICcnR86fPy+nT5/WjdWWsQFyJV8wEBcvL3nImygtKIN85va7cOGC6oEuV3tLRvdgO0r7OBb70q7P5edHIFUeLp1M8/eLnzkCKYMAg8T06dPl6aeflg8++EB69+4tXbt2lZ27dqqONoiMGjVK3n333Xx6b9u2TW644QZZtWpVvrznzp2Td955R3r16pUvf/DE5K5Zs0YmT54s06ZNk+XLl8u6deuEuKu5rV+/XhYsWCDHjh3L166g/lfi2DA6e/asbNy4UdgTLP5K6FCR6zCcT548KQcOHkgJ7J1MK/IV6W1PaQQYMMaOHSsfffRR9F1wyLVTp05y6tQp1f3w4cPSsWNHqVu3ruzbty/ans2bN0ulSpXk/fffz2eF7tq1S6699lp58803Ew78NlCtXLlSPvnkEyXyI0eORGVf7YOdO3fKgQNXdwA1jM6cOaMPGewJFn+1MSrv9RvOkGl2dnZKYO9kWt6vOm9fmUWAAWPcuHEyaNCgaBv2798v7dq1k/2RAWThwoUycuRI+fLLL2XChAnRfFhwWLEvvfSSpKenR+PHjBkjzz77rPTt2zcfyUYzBAgBq3bo0KEyYMAAOXjwoGYJun7R70pu5k7dvn17VB8bVIP6X4ljqxcSBeurQabWF1eivalWh+GvlulVfrAybJxMDQnfOwIphgADxsSJE+Xll18W3LaQ4sCBA+Xzzz+PWkC4bLEgSXvttdeig/rq1Wukb5++8sUXXwgESoAQP/zwQ/nuu+8usViDTbeBCjIdMmSo9O/fXw4dOqRZLC2Y/0od50QWXjmZ5kf8avZJfk2u3Jm12cn0ymHuNTkCKY0A63JzJf7qXAYM5izr1KmjhNiqVSt58cUXhcVABL5a9vrrr8uZM6f1nGPm7whr166VLl26qNXUrVs3XbzEXCPkytwnxGsDkhYI/LN4J9MAKDGHhtGVtkytXtTBlX/o8GHVLBgfo2qB3oPYvGXl3NrrZFpWesz1dARKEYFEJGpVMmDg5sUaJUCeuG5tjoiFQU89VU0tx48//liqVq0atUJxPXbo0EGOHz+u6biDBw8eLBs2bJBNmzYlTabJunlzcvNW/qJ3cAumBY+DeZI5tlW82yqomxeMCOznzZsnTz75pPZjSXsNwNlc6lph5B/1xosP5rlSx4ZFSZMp7StuG93Ne6V63+txBAIIGJEyPKaf2C0XcuO/8sI8KHOWFoYMGSLffvutnrIiF2sT9y0bq2whUF6j2bp1qzz//PO6yhRirV27tlqxDEJYrcksQMIyhYD79OmjpGw6XO09Lm2bw7VB9UrrZPVeKcvU6qOdkF337t2VTGvVqlUoobJYbe/evbJ7927JzMzUPd9kP3Qw7LpHpslnP3zEcJk5c6bGce39+OOPceHlOnrvvfeii+FMRtzMJRxpdZUkmQZJNHicrOpOpski5fkcgRJCwIgUcVOzFkjN2XfL7P1LVbrNC3LCgMFrL7wSY4HVuCxAglDbt28fHchIZ5Dt3LmzLF2yVF2ANWrUUGJlMH3kkUd0rpR8y5YtU9K1Aclk297iycf8LK5hiJq6ma+8mhtEipXNKmaC6Wq6F7Qnb0FbQWVj06zeK0GmVhc6YJGuWLFCIJEePXoooWKh4m0gBEnAykGGTZs0lX59+6mXA08Hc+fIig1cmzyw4fUgQJiQMAHMecCy14BYDMc57x0XFkyXwvIlm27ySopMDTe8PzyIEiwuWZ2cTJNFyvM5AiWAQH4iXSg1Zt0rXde8JQfOhl89CaZTHa+kmBXGOYMIgxi/9BR9PYRZ14gLkAGPMlinWCPmGkWGvU7DHhmFBfKdOHFCTp46qQMpMlJho43WrsLaUNT0WPwTlTe8S5tMrR704CHiqaeekkcffVRJDCLBQo1HiuS3sjxcDeg/QPsS3JhzZwuSBceQIvthw4bJ1KlT8zUdWRAnr2Fx7cUGylmfsLfjoB4cU6+l2T5WVjLn1raSIFPDgfuFle6//OUvo4RaFB2dTJPpOc/jCBQBAQbkeINyMG5qFkR6n3Ra3VuOXQi/Mxq0SotQXZGy2iBUpELlIDMDJiQAEcduPHxgkZjFlUxzDcfSJFOrA31w59esWVMH+yZNmiihYqEy2AfzBXW3+MWLF+urUPYwZfGWF2sftz8bXog33nhDZs2apbJ5hYryeCZYOc7CNebnmbdfs3aNunkh4YyMdPWgsGAO1zAr0Dk2MgJjpgwoz55XufC62GK6WJ1Mt0R7y3+5ZBokUnDl3Wy266+/vsiE6mSaqLc83hG4TASC5Bk8DhPpvUqkx6NEmv9zgFY1g4YNHLFxsfGkW35dJRz4hi+Dhg0clsfkJdpbvlTcJ9K5oHjmASGkBg0aKCmlpaVJo0aN5IknnlBrzMiU9hYWLE9pkanJRw+IFJd9w4YNhQEf6wkLNWiRBvOb7ha3eNFiJTgjNktnD8m9/trraonykMH8OkRoZMqXtxb9uEiLsFL8rbfeinpK+CrW22+/LXxVKyMjQ3UbP368ekyQw2I5VhwThg8friTKh0Ugb+ZaR4wYcVXJ1O4HLNKmTZsqiaIXXxODUP/85z/Lli1bVH/LqycJ/jmZJgDGox2B4iKw+3S27DkT/sgBA1o8Iu2czyKNT6TB+pHDYGgbN3dwyNd6EpCADapBeckcU456gitwg8dWp+a7Aqt5rb5kBrZg+yhnYd78efLrX/9a7rrrLnnggQd00Pzss88s+ZIHl2hCzIHJLA0yNdlUaUQK8UOkECoPBLh8LQTzWxx7i1++bLm+JkU7sTwhNqxCdOc1qZ49e0bfT6Yc+WbMmKHXGl/fWrQoTKYQI2QK6RKwjN979z11D0OQnTp1jn7mkXRWgkO4TA306N5DMkOZWo5/xONONoI3XaMZCjmw/MW1TK085G5EStvAhI11CkaoNodqZRKp5mSaCBmPdwSKgIAR5qmcc/L8ytek1dLOsu9sZLVkZDCP79otnEiLoMYlWW0ASHae9BIB5SQCHAwLiOi2226T6359nS6wsibyoJBsMFklTaYmFz3MtWsWKYSKhUq8hWB+i7O9pTFn+mavXtHvK69evVoXLEFkWKDDhg2PWojEQYLFIdNXXnlFjh49qtUj59NPP5U1q9cIn39kbpf5dwssboPUrwaZGi4QKdhCmljY5gZHR44hV9J4+OKjKQQra+0I7p1Mg2j4sSNwGQgYoS7NXi015/yXtF/+quw9EyZUVu2y2Ig50sJcu0EV7OblfdE5c+eqO46vIvHVo6CFxnygDQaUYYMcbLDCEuC1GZMXLBusj2PLw2CD+47XKQrayMMK3x07dpTqSt+gfFyLxQnWNsjC3t8NtjlZmSanpMnU6jeL1IiUfVGINNgm5jz5ipXNT1od7OfPmy+DBg+KptEuSDARmUI6iSxTPl0ZS6YsWuLaYeUxLmULXL9XyzK1vuN6giyxQlmwRyDN0oljHpk8rGq2dD2I88/JNA4oHuUIXC4CKw6slxqz75ZXVr0p43bPkhqzHpROq98MLDZKzgqyGxs32m9+8xv9FZmlS5fqIhHmnCBFBkleZ8BllyhgjTBoFESiVtbqXLJkiS42YXDFWondiIeQIHcGUVYXl+ZqX+TzazG4F6mHYLqa7snuKWeEXBwZVqY0yBTLGeKMde0ma5EaBqYjlimLhqy9ls6eByFep+LBicC8McTL/DIPYhwvWbxE03j9BmvNfrEHQvzow4/UzYscCDNIplyfPMQhk2uP68nC5CmTrxqZmg7sed/WLGbDi3g7Jo08yQQn02RQ8jyOQJIIMDtn7sIVB9ZJzblPSvWZf5POq98qMpFSpd3UPN3zOUHmiAgQKKsube6M1ag2yDF44VrDWrSBAguBzw0SIFQGCLNkNTLwz+qkDCsvmUODOGM3LIuBAwfowBsoXuqHPFhcDpla+1A0eFwUxa1cSZGpyYN8qlevHl1sVFTXbrANJpNrpGWLlvqeMR8BmTB+gnz//fdKbhDmxAkT9ZeI+IUiXA3j5LkAACAASURBVK+NGzdWDwhp+urN3PD7qBAurlyuCR5seKjr0rmLkjRWHuXM+qQsK4HnzJ6jKkGkvBf91Vdfyddffy184pJjs5ZN16D+BR1b/uLOmcbKNnnB+GBc8DiYJ3jsZBpEw48dgRJAAEK1mw+Xb7d1H8qxC2ESNKJNthqTA/mxitM+HUf5yVOmqOXAcbfu3fU9QAYxrFQGsn79+umvxuCuwk1lZDpl8hRddGLka3WYTnYOmfKLNQWT6UB1CVIWkqZsaW1mVfOQcDlkGttOOy/K3jAqKTK1to0ePVqt0pYtWyqhFtW1G2yD6chqVRYRQapYt+xZCczrLgRebeF47ty5OjfIQiMsTXQiPvheKaRJPl6N2Z8d/mgD1xwWqVmhyKRuLNmsPXnvpFKWelnpiwwexq42mdq1GsQteFxYejCvk2kQDT92BEoBgdM54fm9ohIpqtiAaGRq81Wk4YpjGT8DEkv6GQSxYBmAjXT5+g1lcAHjamPBCa87mFVq8oPNtriikqmVC8oqyWOTX1Jkejm6mS4lTaZYbTfeeKN+Z7latWpRzwO6Wp1F0bs4ZeLJv1w5XH92zSEfIuXXi4obTJ+SskyLq0ewnJNpEA0/dgRKGAG76YtDpKhi5SFT3ok0kiSNRSJ8Fo48kCrkZ/G40Xh53t7zwzKlfLNmzaJzV1gU8YLVaWQa6961cyxW6kAPgllX8WSWRJzJL49kaphjNYIpGwuHLFi6nRdlT1n6Gvxss3PkkE68xWmeyAp0joN1Wz7irFxQRlAvlZMTXhvAgx+v4OBKZp6d70rbZwqD8oPlCzq2Mk6mBaFUCmnW8byYZ8e+Lz13nGObH1uItLiYMCARcLuxojNIprwDOGnSJE1nYQiEiesWtx5WwPIVy6XRs42UUPm1GBaa8H1dvkLDHCvBBsugflbnyhUrdeBj4RGu49gNUsWVPH369ISygnIv99j04jUF+5RiPP0vtx4rHxwvtIGBf+QhlJRliiyTGaimXB3Sb/MXzNeHBPOwFLfNVs7J9ApeIoDODYcr7OyZs3rxM4fkm2NQFq4BSJFrl4GIxSjsmS/EHcirCBzTDp70WbGLJdqiRQvNx2KQV199VS1R0lhMgvXxww8/aH6Il8VKsThYnfZKBfOmtn3yySfRYxaiGKEjl3KxskryHPnUs3HDRrVqwKUk5QdlQZJs9r1aI3IbumwwBz8eVNgTLN7yFXVv45U9JBS1fFnKfzlYWVkn0yvU43ZhsiScJ3KexnEt7N4T3vQ8cBx7Tj7iglu8uGB6vONgffHSY+OKU0esjNhzkxnUxY6D+9hyxTm3uihrx7Y3ecHz4LGlB/ekF5YnWFfscaJzk2uyo/vINWLlLD7eucbF5CeuoC0oL5iP+OBmsm3PKtZQZqauxGW1Lq5fFodwTWO5Ml9KXvIFN+JII468lOF+sPwqP3Ctm36kIzcjlKF1UR/n7PU4cB4rg3PbTJ6dJ9pb20m342BZO0Yv2pFITqJ4K2/p8c4tznACZ97xtbHEhi4bzCFc3OHsCRZv+XyfhwAPCDk5YXfz5eJk5Vmtbq/1WFxejVf2qNzOmQKsWaQ8vXADeXAEHAFHoCgI4FbH+sciZosdsInD5czew5VH4Nz58/kWNl15DfJqLNdkygWOVYq7iydNAjeDb46BXwN+DRR0DZhbFyLF8mEciUemeUOpH1V0BMolmeqL85HVabhfuCGCZFrRO93b7wg4AgUjANESGDtwizOfyhxtvLlMy1uwRE8tLQRSBf9Kpgh7+7YojQ4elwQIRZUXzM+xnSc6Vp0jNwBt4aJn8QCLFvghZCfTkuhFl+EIVAwEbFy0B3HGkVjr1PLEIpJorIrNFzy3MsQlOi4oLVjG5BKXSEfLU9A+KDN4HCyTKD6YJ3icTP5gnmSOg/KLehxPfrw4kxtMszjbl0vL1BqHWwbLlDkNJ1NDxfeOgCNQGAJGQpAp6y2wTH1etDDUKnZ6peMnjuv3PlmkU542VuAxV8pnr2zlIl1tN0nF7nZvvSPgCBSEgI0TLEDi9yyZN2U8YVxhBWl5Giu9LSXDfZV4wVu/s7h/v7pDs/dnR7+7qMeRc/JwzvcY9Zhzvs+4P+88eKx5kRnJT1rwOCjDZAfjNH9Eduyx6ZUvPjuif0Qn2sUTJa8D8B4Yy+kJdpMUdCN5miPgCFRsBGycsE8x8ooM3i3GFcad4Nin41DMuGhjWbwxT+MYSxOMnbHxlj9Yp8m3fWwZyxuNT6I+8sZuQfnoYemXyI/wgY7NQW4wPgnItrK2V5kJeIK0WB2snMUb1+h5gK9iy1p+jY/Ry2SqLhFdLS5YLm5/RnR0N2/FHjO89Y6AIxAHASNTd/PGAcej4iKgC5C4cMrbxvyGLUDiadLnTOP2v0c6Ao5AHASMTHHz8oEKXLt85YhxxVb0lrcx09tzeTxYLi1TLgoueJayswqP+Q4n0zgjhkc5Ao5AXASCZMoUEfOKsat54xb0yAqLgJNphe16b7gj4AgkQsDJNBEyHp8IASfTRMgUEo/la5vdeIUUKdPJZu2nQiPA/UoF2l0R+vdK4VlW6rE+x83rlmlZ6bWrq6eTaRHxt5usiMXKdPaK2OYy3WGu/GUjYNe8k+llQ1lhBDiZFqGr7QZjMcKXX34p/Ibkm2++KStXrswnBcuJhQpsVoYMZslaullY5LGFDfHKWbrlCVZmsqyuYF6LC+Y3+cE0fm/T4k0nK2P6z5kzRyZOnKjR5I3NF6tHsHys7EQ6FiYDmbzrx+9oHj16VKsw/dhbefZWR1AP4gnsbQu2xcoEPxs3f/582bZ9m5azvNYe8lsZ4jgOBuqwMsF4P059BKwvnUxTv69SRUMn0yR7wm4uFjTxO5IffPCBLmpatHiRPP744/qbkYiyATso1soG4+y4oDTLE7u3MraPTeerTz169Ij+mgI6WV6O+XFo3p0iMNjHBstLvLXns88+k7fffjs2a8LzoIxgJpPHCuvXX389mmTx0YgE7wTzG5xPVXsq+uPQ1JOoLpMVTA8eWzp7q3/79u3Sp0+faNK0adP0J7aiEYUcJJJfSDFPTjEErB+dTFOsY1JYHSfTJDvHbq558+ZJq1at8pHQjBkz5Pnnn9fVw4jjQxHjx4+XyZMn60vexDFYr1ixQn+8eeHChfL9999rPtIg6B9//FEYyKdPny5TpkwR+yV60nnFZ8GCBVpm3bp1REUD58iaOXOmLt3nCy1fffWVVK1aVSBAPqVoAZIdO3asPProo/Lxxx9H64fY0BWd0Z1g7TWS+eabb5RkqO/bb7+VNWvWRPOQf+3atarHrFmzoiROPJ9hw6r97rvvZNmyZSqbtvXr108fQoi3thpu4GmWJwVoP7iDC9h16NAh2i7Tj5et+V1JcARn2sQxZQms6DYPwpYtW/SHtGkD9fPD2QR+q/O9996Tp59+WvGgXzZt2qSywIN8nKPfpEmTwi+TH8hW3CBddLCAXrQX+dRreNre8vk+NRGwfnIyTc3+SUWtnEyL2CtYLWPGjNFSNpDz/pkNpHxtqVatWjJu3DgltcaNG0cJtWnTpnLHHXfI1KlTZdCgQfLggw8qaeC6rFSpkrRp00aJp1OnTvLqq69GXYSDBw9WAqFctWrVlFBQAAJNS0uTuXPnSq9eveSNN95QPSC0OnXq6ICPJWcB9yVuy3r16smoUaPUZcriCvJ+/fXXMnbcWE3bti3s1mRAsTZCoDfccIO2CdK9/vrrlVCRjfsXPWbPnq3WK3rYO3kDBw7UOAj1iSeeUDKHpKi/fv36qjskzxdmaBv1QGi0n3wE2t+6dWuZN3eedO/eXeUwyBFMP4gRDDt27ChLly5VT8Hdd90VlbF4yWJ57rnntMyIESM0L22mLX/4wx+EhwQIHBdys2bNZOmypVq2ZcuW2l9g8cILL0iN6jX0webdd9+V6tWra9voBzwBXbp00YcHKhk9erTQ3xAv5MyeYIO0nvi/lEXA+snJNGW7KOUUczItYpd8+OGHam1QzG44E8E5gz0WlIWhQ4cqGXDetWtXGTd+vCbhXsWaxdLhHTZcxRs3btQ0fvKpQYMGOphDzo0aNTJxan0xTwsBt23bVsuTiAX2ySef6CcUz547q6Ri1h2EY7ryrhxkbT+WPmDAAPniiy+i8nkIgBiMpGyPtYt72MKQoUMUB3SHLPh+KQH5kNbixYv1RXceHsyaZmCCVAm8CN+5c+eohY9sHgIskAZB8pBSs2ZNtSxJAxtImC/TEEy/9evXK9kZAWOl8nCCZUzgvHfv3noMkUP4FugjiJVAH1g+ZPd8o6c+gJBG/KJFizQf8+Z169RV65cI9Klbt666/rGC6T/DH6whZcoQrC/0xP+lJALWR06mKdk9KamUk2kRuwWrCVcpgcHWbjrOcVcygO/csTMqFdcgAzdkx1wr1hsB0sGahEwZZLHKcDMSIBBcmbhsyY9bdsKECWppvv/++9K8eXO1vNq1a6ekqoUC/3DtYqExqBPQ0fREZvv27dWde+HCeSU+SMsCukP65CPYnOrIkSMF4rWAdY5FCok+3+55OXE8TBSkY5XhFiagP23DEl++fLkV13K0EbKjLlznffv2lUkTJ2lbb731VrXmeJjo1q1b1F0LabVo0eISMgVnFoSZWxfyxDI0csXVanO0tKV///5RXbCGzdtAOfJhxdN2Ho6w/An0o2FFn2Gp2jl9D4HykIDL+7HHHlOZuIOHDRsmv/jFL/RBADnWF1EF/CDlELA+cjJNua5JWYWcTIvYNazixZIhmFXEXB/zlpAgJLZjx46oVCw0JdMLF5SkcAkSIFMGbSPTJ596MjpfCQlClAzYDOQcQ0TMF7LH0sEVi+sTC9WCER8DANanLTIKkqmRAMRNfvJBRBY2b96sbcDiJJhMCAiyswBZQvC0vd3z7dS6trThw4erG5dz6obcITMscdyoBOaHX3zxRf2JPOqCmGxelblOLE1IFt0gNMiNQHux8mItU3towb1MoD7y4UImQHA9e/bUY6zs4CIjLFUeAAiQKZY/7WaLJVPSCeDIQ4mdgzkWM2TKAwBEvmTJEu2zZcuXaX+ZlawC/F9KI+BkmtLdk5LKOZkm2S12c/Fzbg899FDUrQmh4qJkdS+BfZBsu3V7NTpQM6cWtEwZtCEvBmbmWW3xj5Ey8RAzc5xGmlhaGRkhJWOI0Kwm0nGNMphDQszVmmUatKDVCmzdSskMfSFJ3Jf2YID1GSRNi8cNGmuZ4hLGEmS+lAVSBIgTSxR3KYuAsDhNdx4GWBhFgEx5GDDLEYvfrEPSwYI0SLNGjRqKE/EQFXO8kBfB9MNCxDLlIYXAIqPatWtH8/GwY5YpDwKxlinWKQFyBFfkslGGxU8EcLIHD/qGhwE7xzJt0qSJ6k17qdv6E524buzBRIX5v5RGwO53rjP/aENKd1XKKOdkWoyuYBHPk08+qa5LXJVYnkYYEAhWFi5cFtGQZlZeg7Q0XcxClcxrUpb5RAjuuuuui1q0yMBlaCtxWWkLoUDSWDz2vidEDNFCcsxTQkYMAuZSxh0KMRNscMjJuahEwnzfrp27lLBwo7KhM0Ri9VLGyIq6SbeA9Tni8xF6CpFhlbFCF2vQ5h8hD+ZjIRncvA0bPhtdPMV8Igt93ugZxg49mQPmwQRixeoDBwKLd5hTZjFT23ZtdRGX6Wj6sYIXcjM3L/uPPvpI55spx7wr6QTaQr9Y0LaMCLeFOu+//36tC8Kkj2zxEF4Hc1XTZ8yR2gplSP/uu+9WEkcuD008IDGPTbt4aDEytb6w+n2feghYHzmZpl7fpKpGTqbF7BlcqJAZFodZQ3YDYlHhhsWqNLcjaViKDMIESAACwfXHIIvr1vJCBOQ11yb5GeSpzwjG1OZmJ56nZ6ufNOpBByNy4iwd/bAM7ZUU6kVX8pulaHmtHvIagRHHw4M9QHBOejw9kBPKDMXVnTLoYXUabugR6xJl4RHxtBfcjDRNT8rSJ3aOTrh46R9WCqOr6V9YW5BDGerg2PqMek1X+oy+sHP6Ch3NrUz95DdMOCcE9YtE+S4FEbB+cjJNwc5JUZWcTIvRMXajBYtanO3jpVlcvDyJ0sibKH+8+HhxJpt9bLpZdgXlyZX8X/YJ5o0n0+Ji67J43cfITEYPyiUb4tVdWNnC2mnlY2XHO4+No2y8OJPp+9RCwPrKyTS1+iWVtXEyLWbvcLNBAHyKz248ExVNi1ntS3wwb/A8GI+ceOfUV1B8kAzIF4+gTHZQluUNxllbbE+eYN3xzq18Pj0kXM7STF5QD4srSA9Li603WJa0YLAy1keWHisj3jllCMG04HFsWvQ88JBA/njtVsH+L6URoO8ITqYp3U0ppZyTaUp1hyvjCDgCqYCAk2kq9ELZ0sHJtGz1l2vrCDgCVwABJ9MrAHI5q8LJtJx1qDfHEXAELh8BJ9PLx7CiSaiQZBqcWQseJ+r8ZPKURtlEMoPxQd2Cx8E8fnwpAkGsgsea85KIS8tbjGYtQn4rV9C+hMVdWlWpV3BplakQk0yzLY+TaSr0WNnSocKQKa+OeHAEHAFHoCgI8P6wf7ShKIhV3LwVhkx5J5B3AXknlPcq2fMeoR87Dql8Dfh1enXuUcOd95P5qhjvaxPH+8VmtVZc2vCWx0OgQpDp/uxsfXk/M5QpbKGMkO792HFI9WvAr9mrd79mZmTqJyH5oApfw3IyjUchHmcIVAgyzT6QrV/P4VupfBHHN8fArwG/Bgq7BjLSM2Tb1m36ZSsnU6MM3ydCoGKQaXa2fraOmwNC9c0x8GvAr4HCrgHGCz53yWcinUwTUYjHGwIVikwLu3k83QdYvwb8GrBrwMnUaML3ySDgZOqWqlvqfg34NRDnGnAyTYZCPI8h4GQa5yayJ9OC9rHzLQXlLQ9p1t7SaEtpyo6nL/XFi/c4t0qD14CTqdGE75NBwMm0GGTKYLwnc4/+BFdW1l5dHZxqAzS/VRocGILHpBVVX1aV7tm9J6HMoPyiHiN7d+buUpGNLrHtpb6i6uj5Kx7ROpkmQyGexxBwMi0imXKDMRivWrVKZs+aLQvmL9AVf8QVlaBKa4AOpYeU6HkFKLYO9OedW5b9J6svZdavWy8rV6y8RF6s/KKeI3vt2rWycuWqEpdtumh7IwQKsW7auEkJ1tJ9X/GIMpk+59r0BUhGFb4vDAEn02KQ6XfffSePP/G49OrVS5o0aSIdOnSQtWvWKskaQUFkUTLbFR6suDm5ifOlReovKA2ZpFOOvdURjIdAOSfP1i1bZfz48bJl85Y80twVrnfH9h2atmH9BrUGTVZQJ4tDV46xvj/99FNp2qxpuO5Ie+KVsbLBtODAFYyH2LB2+/btKx07dszDK4AJ7Y3dTJ7Fc84x+6j8XXlxUyZPUbKmHevWrpNWrVvpQ5BZw5SlHHv0D55bXbaPyi/idWPlfV92iJvrwMm0MArxdEPAyTTJQZFBlsF34cKFcvddd8usWbOUZIjv+EJH6d69e3RA5iaE0HhHLThI79yxUwfq7du2azr52JBhaZQjnXI28GL1kg45kpc09uauJB6StLoWLVokVas+JgsWLIzKt3JYl6TNmDFD5VM/5bZt2ZZPJ6ubcll7smTklyOlU6dO0foTtdF0QKftW/PaQX70BRPSkE/c7t27ZciQIfLaa6/lazPpkC172sbGOThEdcNdHXFZW7zhh2y2jRs2yrPPPitjxozRc7D98ccf1Tq1OpCBTsigjznfvHmz7mkP+ZDFcWy/mi6+LzskmWxf0edOpkYVvi8MASfTJMmUGxAywIrq9UavqFWHZcXgPHDgQB3wt2zZIu+88440btxYGjVqJIMGDdLBGFLq3Lmzbq+//ro88cQTmg+5a1avkfr168sbb7whXbp0kUcffVRGjRqlAzh1zp49WwmhWbNmWn7NmjVq0eFqhuBat24tdevWlenTp6v7GUv53nvvlRYtWgjEigwGBtybr7zyitxzzz2qmxHqgAED9Byd33vvPf3ABfnRzcj0iy++kA4dO2gcxBPbRggIsqEO2te8RXNp2LChfP311/o5NuR9+eWXQhsaN2msbYWwIOpPBn0i3bp1i5IpdUJqw4Z9pm2rUaOGWtOQLt4A2sMGtljMmzZtUv0hZPB45JFHZPTo0bJjxw7p3bu33H/f/VK7dm0ZN26cYJG3ea6NrFixQhb9uEjLoS8YpqU1lLFjx8rbb7+tHgf0p2+VYHft0vogZuKp1zBKdnD2fGWLcOlfJ9PCKMTTDQEn0yKQKWTx6quvytChQ5XMzCoiHlJl0O3Tp48899xzatlAdnXq1FFiJK158+bSpk0bWb9+vQ7kVf5WRS1drKdbbr1FPvroIyVk3MiPPPqIQMyrV60WyGTChAlKZBBu77d6S0ZGhhLvhx98qIQHMd5+x+2yePFind/E/bxi+QolHciJDQKibkh27ty5sn/ffvn888+lXr16Ws+mTZulVatW8skng6IEEiTT9h3aKzHSRtoBGVobv/nmG325HSKCsBmEsOIrV6ksc+bM0e3ue+6WlStXarvS0tIEgt63b198Mo1YrDVr1pQ5s+eolciDTPcePfTD47SFh4DBgwerHnfeead88MEHWi/4Va1aVdtKH73wwgsyadIknSvGMn+q2lOyZPES7YN77r1HJk6cqPh8+OGH8rOf/UymTZ0mO3fulG6vdpPXe76u1jPkjM46d7xylfYJmNPvYOREWbaIMpn+cjI1mvB9Mgg4mRaRTHHnYhHhngwOogyqkAskxiDL/BwbgzAWKS5EiAp3Y/b+bCVNrKgfZvygrkisqaVLl0r2vmwlKORs3LhRIAYsIdyL1Ddp4iQlw9mz56j1C5lRN+SydMlSgRBZ0NOseTMlLuIpx8YxxA2pQ3QMFu2fb691mL7Tpk3XuVHaQjpkhPUI6Xbq3El1atL00ja+9NJLsmHDBklrmKZEzaIfyrOwaN26dYoN85Xm5sUa7N+/vxIceMZaprTp448/VqyRtW/vPvUKUI5f8aAteAOwVrFMq1evrm06eOCgrF69WurVq6sPCOjw4osvypQpU5S4IXOsVLACA/pk27Ztqse0adOkZcuWivXeSN9RFhdz2+fayvDhwxVHXMVYyDxU8JCUzMDsecoe2XLtuGWaDI14HhBwMi0imeJKVDKNzK0xSOL2xFWLJYir1OYqGfCnTp2qZMoAjMX61VdfKclu3bpVB/mZM2cqwT32GHOcCzQNOSz2gZyw+KpUqaLWFe5biBDrD0sVNzIuXyO9A9kHlDAg2BYtW+jq23hkCtHivkQniBryJx9y5s+fr3riDsXiDpIphAkZUW++Nk6ZKqThOsUNOm/uPCUZHiB4OMD6pK5PPvlEWrdpLT169JAHHnhAXaWQeEFkCmGiV9aevdK3T1+dW0VXdAuSKdY7Fix1YX0+88wz2if0D4Q4efLksGUaQ6a4oyFjHhggXB4UwH3P7iwZOTI8T8yDxXNtnlMLHlnt27fXfoBckW8PKwUdk+Zb2cLAydRJsigIOJkmOcgxYGKFjB4zWgdS3IBYT1iZuCsZlBl0cX+ykhYXKhYVlhOuYcpDpswhEo+FhmVqZMocKpYSaZABc4sM8shq27atDsRKeBkZ6mrF+mqQ1kCtWQgEcsFqhdSxBCFdVhijow32lDfLdMmSJUogXbt21blM6kXnMWO+VcsXa81IGqL58osv9aGAhwDmFyeMn5CvjViWuKUhU8gZYkcn5nEhWeZLW7ZqqeR89MhRJVLIkHpx1UKw5DdCQm/mUiFg4iHdAf0H6FwrZbAcKY/LHZxq1aoVdV1jDeOSBQvk4eZFJ/qKhwHc2ngBeKDAMqXfIGsefMANjwBtpq/Mq8BctvUduBgxhok+Sx9GiKMc14ldL5xbXt87mRZlcPa8ZQsBJ9MikCmDuhFm9+7dZNmyZbpg5eGHH5ax349VqwjSwOXIoiGsIRYTQSi4hZk/hXghA8iUVzQY5LGEbrr5JrVMcWcuX75cXZGQIeSH9ch8KiQB8UAi6MIcX7t27QRixEqiXggEV+/jjz+uVjCLcBjEGdxNfyxLSJ4HAnR86KGHhNdH0Lla9Wrqig6SMEQzbNgwJRpcrFjXzDsG24iLlHaRDyLjwQAX9X3336f6sbCHeUzai+v7D//zD1E3b7/+/fTBAv1MV372ijlSXKk8BPCRDOYyH3r4IaEuiO93v/+tkin4MffJe79Ywlj2rFjGQue3KHlowZrHg0DcAw8+oHPLeAJwB6tlmrVXH0aervW0Yk6bcW0zv4xO1PdfD9yv1itto/9Z0U0ai5Gw6CHRr0Z+JVOnTFHyp9+/+PwLzUM+38oWBjwouZu3bBHa1dTWybQIg5wREot43n//fenSuYtg2U2dMlWtOBssse46vdhJunbpqmQFAVG2z0d9NC/WCvNwzAliHUHQPV/vqSRKGiQKebLYBVKDAFh4BCm81fstzQfBQMjIwPXYs2dPWbZ0mQ7o6IF72IiWvNRv+rPgBmsXYsPi4xxd0fnbb7/NN+hTBh2weiFxzpHP3G+wjZAWgw8EPWLECHnxhRd1Ac+8efMEYsTSxYrEckfO4MFD5LPPPlN9Id3g6ljqgJjQBSzRnzpxOUNwuFlZdcwCJFbogt+bb76pi4ogdOaM333nXX2nlPbN/GGmegVwjVteMIV0wRmLmjaiK4uYyMM5Dxjoaq/MsIjJVmTz8ILrmo2VzWDJwwD50Rk9eMBCPrqDDXvfyg4GTqZXk5rKXt1OpsUY4Bg0GaTZGDQZeIODJPNtxMemkd9cgOSHOCEKblrclshVwksPyydezzPCXzSyOpVcIh8lUB3QI2tvlHSQjU7Ub9ZePv0in0I0krW8sfpGy+xKV72DLstEbbR2Wftpb7rpuieMC1aftiXiAqX+oGyrl3g2Ow/KNiyQD06cG352bviRB31i81o/Wj7wQA7n6Ez+oF5RnOj7fBbcvAAADN1JREFUPVlRgqQMeVW/rPD1QL9pu7L25tM/2BY/Tm1i5Tpwy7TskdrV0tjJtBhkyiCIlRTdYl6NYCCNl6ZxgbyaL3JOGgO4DbB6HtAtKi/mm7sJ6zIdAvVFZcekJZJh+bW9EcvW4goqkygtGh+RxXk82fnqiNE/KiPysYaojMh5tGwAp2gZqy+CtcVHy0RwKez8kn4M1K0yrZ4YzEyu7/Ou81TGwsn0atFS2azXyTRAWKl8Y7tuZWMA9n4qP/3kZFo2Se1qae1k6mQatYadCMoPEXhfXn5fOpleLVoqm/U6mTqZOpn6NeDXQJxrwMm0bJLa1dK6QpEpN4c/sV/+E7tj6BhWhGvAyfRq0VLZrLdikOmBbH01I7iIx48Di6SCi6n8OG/xmGNRsbHYtUv4SEnW3iw5ceKEnDt3Ti5evCi5ubllc7R3rUsVgQpBpnwhiHcdDx8+rNvBgwfl0KFDgeP48YcPBeMTHceXEyybCsfB9paUPocS4hPEJP5xUIegnGB88DgZ/RPJCZYt6nFQh0THiWQmkz9RHosPyrY4rt9kjhOVTRSfSGYwf/7j4D2R18+J5eTlL6k8ifo8kfxE8fHadejgIcnOztZvQZ88edLJtFSpqOwLr1BkWva7y1vgCDgCVxIBHsD5IImT6ZVEvWzWVWHIlM/5EdxFUzYvVNfaEbiSCNg4gReAL5g5mV5J9MtmXU6mZbPfXGtHwBEoRQSMTHH/OpmWItDlSLSTaTnqTG+KI+AIlAwCRqYHnUxLBtAKIKXCkWkF6FNvoiPgCJQQAm6ZlhCQFUBMhSFTXDUElrbn5OT45hj4NeDXQMJrgHGCcODAAXfzKhL+rzAEKgSZ7t+/Xz/WcPz4cTl69KhvjoFfA34NFHoN8G4pr9SxeNHfMy2MSjy9QpAp75naal7vckfAEXAEkkUAN28o01+NSRavipyvwpGpLSyoyJ3ubXcEHIGCEbBxwl+NKRgnT81DwMk0Dws/cgQcAUdAETAy9QVIfkEki4CTabJIeT5HwBGoMAg4mVaYri6xhjqZlhiULsgRcATKCwJOpuWlJ69cO5xMrxzWXpMj4AiUEQScTMtIR6WQmk6mKdQZrooj4AikBgJOpqnRD2VJCyfTstRbrqsj4AhcEQScTK8IzOWqEifTctWd3hhHwBEoCQScTEsCxYolw8m0YvW3t9YRcASSQMDJNAmQPEs+BJxM88HhJ46AI+AI5P3usb9n6ldDsgg4mSaLVCQfT6x8KN+eXIPFC0oL5ivPx2AQD5vy3GZvW/lDwK5hJ9Py17el1SIn09JC1uU6Ao5AmUXAybTMdt1VU9zJNEno7ebauHGjvPLKK/prEhQl3tKWLVsmPXv2lOzsbJVKPFYsP+fEZvmCPwFnPwkXVCNeGavLZJkMk0m6lWOfKFieoD7xZFt55AfrtHj2QVlW5969e2XatGly7tw5zZqoPPltKwoGwfr92BEoLQTsvnLLtLQQLn9ynUyT7FO7uRYsWCCVKlWSMWPGaEmLP3PmjHTo0EHTMjIy8qUFq7D8wbjgcbz0eHGFlQmmF3ScK+G/2DyF1Rmb384h0y+//FJOnTplUZfsiyO7OGUuqdgjHIEkEbDrzck0ScA8mziZJnkR2M31448/ysMPPyzPP/+88PuoFrZu3So1a9aUxo0b62+nWvyaNWvku+++kzlz5kQJJj09XVauXClYuaRh0V64cMGKSCgUknHjxsnkyZOjVi6J58+fl0WLFmmZ1atXy4oVy+XIkSNaDutu6dKlmrZ8+fKorNgD6jV9Tp48GU2G/GbOnCljx46Vbdu3R+N5SEB3yqxYsUKtVEs0/adPnx7Vg8GHNqMrAbmzZs2S77//XtauXWtFZdu2bUIbVq1apWnsgyGentYHwXx+7AiUBgJ2rTmZlga65VOmk2mS/Wo31+zZs6Vfv37y2muvycKFC6Olhw0bJu+995506dJFtkfICGKqW7euzJ07Vzp27KjlKIAbFOt26NChevyXW27VPKStX79eHnzwQZk0aZIMHjxYmjZtqj9iTBrW8JNPPino8P7776uMnTt3qg6jR4+WRo0ayQ8//KB1TpkyRePR23SfNn2aPPfcc6o3DwO9evVSEof4aA/n1Ev9W7Zs0fIfffSRvPvuuzJv3jx54IEHlORJ4AEA3dCld+/e0rx5c3XtQqQ33HCDkujZs2ela9euigv56tevr4RN+W+++Ub1x4oFpzvuuEOJlbSpU6fm0/PNN9+MkrO1RZXzf45AKSFg15mTaSkBXA7FOpkm2al2c82c+YP07dtXLTXIk4B1CFlCrp06dRIIjvwQHG5PAvOoEOuxY8eUmMgP2RAmTZwkAwYM0GOsOKwyC2lpabJ582Yl1HvvvVd27dqlSdTZvn17ycrK0h8+b9CgQdTyzczMlBdeeEHM8jTd0e3rr7/W8sxXUhcWMUTZrVs3q1IJctDgQWp533XXXWppknjgwIHoA0SfPn2kf//+gTKz5MSJE6prq1atlFjB48UXX4xa3Zs2bZIaNWpoPqxu5p4t8GDx+eef6ynu8qCeWMaxbbFyvncESgMBu2ecTEsD3fIp08k0yX61mwsCeuutt5TEWrZsqSS56MdF8vbbb8u+ffukRYsWSqYmdsmSJTJ27PdqlUJ4uIax0rAETSbngwYNsiJKSJT56quv5M4771RLF9dvs2bNlIzJCHFhBUOmuEshWlypEydOlM8++0wqV64sNneLC5gAKaMDliTtOH36tMZjVSMbq5St5xs9pUXzFnL2zFl18WINf/zxx+rm1QIiAmG3bt1aXn31VbUkzeWNKxcrFdmffvqpPlBYGXTu3LmzZIQytB6sXguQ58iRI/UU93FQT1zNBMPLyvjeESgtBOxaczItLYTLn1wn0yT71G4uSIgVuxAUFur48eMFKw0rDKsTV+uuXekqFYKEMCAxrE3I5+ixY0qmWIK2Apa5SiPTGTNmqHXLHCKuVqw0yu/evVvnY420mIt86aWXlEwhMCxY5kzRgzlTXM3BRUBWFzoiD6saHXDx4nLt3r27ullZYEXdELHNe2JVo3+7du2U4E0W8qkH0oRA0Q3ZTZo0UTLFhTtq1KgowkePHlUMaAukbZY9GSBSHh4sBPV8/fXX9eGBNOsHy+d7R6A0ELDrzMm0NNAtnzKdTJPsV7u5cDlCpgSIAzcoc4dYXdx4WKZYbRDHY489pnksL+5P8iEDgjBSwjKFkAjMaY4fN06PceViMbK4CZcwbmIsXQLu3nr16usrOrhf69WrF7VEIUHS0dn0xlLErcqcLGH//v1SpUqVqGWLlW2vsxw+fFjT9+zZowutbJETi68gbUiUOVvmggm4YG+//XbZtn2bLixCZ2RB8uiFPALtpDz6TZgwQR9CNEFEiRS3eG5ujs6zBvXE6mbRFsEws3K+dwRKAwG7b5xMSwPd8inTyTTJfrWbi8VDWGgM6hBctWrVolYlbt5HH300ugAJi++JJ57QBTxYmDfeeKO6grE+27RpEyUGFtyYlYZ1ed9996krFmvxV7/6VXSeEovznnvukQ8++EB69OghtWvXjpLM/Pnz5amnnpIhQ4YoIWPpmXvXdMdqrV69uuaB9HGtkodt+PDhalUzd9mwYUOBOCnHPCbWNnIhRlYTE9atWyd16tRR6xzXbZ++fTU/BMoCJpvjHDFihEDULNrCdYsLl4DVShssUC8bgbbE05M0a4uV870jUBoI2HXmZFoa6JZPmU6mRexXXJlYdXazHTx4MOqCxOJiwZHN8UFSzHXiCsUitTSOgzKQiRwL5MMaxaLjZjbLEGuPcsyTYhU3b9ZMrWArhzuWeCzjRIHy5EEvI1vLSxxpWLrBYPE8LAQD+pEfK9hcwlit6G+ywcnKm4WKDNoUrIe0YHo8PXkj1oMjcCUQsPvbyfRKoF0+6nAyLaF+tJvPxMWeW3xx95ATc4pYb1h/L7/8slqLVo/tg/Jj42LPyUtcvHhLC8oLHscrExsXe55IZjAfx8FzqzNenKX53hEoaQTsenMyLWlky688J9Mi9m3sYB/v3ESSlpMb/mxeMF/wmLzxznEjW7zNE2LRsgCKDyjgCjVrkHwmx8qZDrF78loeK2d5gmkWx76w+JwAAZI3KFe/rxSo0+Reki+2XKBMUJ6V970jUJoI2DXnZFqaKJcv2U6mZaQ/7eaOVdddn7GI+LkjcPkI2P3mZHr5WFYUCU6mZainucFx99pmN3wZaoKr6giUCQTs3nIyLRPdlRJKOpmmRDe4Eo6AI5BKCDiZplJvlA1dnEzLRj+5lo6AI3AFEXAyvYJgl5OqnEzLSUd6MxwBR6DkEHAyLTksK4okJ9OK0tPeTkfAEUgaASfTpKHyjBEEnEz9UnAEHAFHIAYBJ9MYQPy0UAT+fzkcZt9pJoNEAAAAAElFTkSuQmCC)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "z0L95Ko61LtN",
        "colab_type": "text"
      },
      "source": [
        "Having connected to the EPI2ME Labs Server, before anything else we will create and set a working directory:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vPF_Wj3_YAJH",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# create a work directory and move into it\n",
        "directory = \"fastq_tutorial\"\n",
        "working_dir='/epi2melabs/{}/'.format(directory)\n",
        "!mkdir -p \"$working_dir\"\n",
        "%cd \"$working_dir\"\n",
        "\n",
        "from epi2melabs import ping\n",
        "pinger = ping.Pingu()\n",
        "pinger.send_notebook_ping('stop', 'fastq_introduction')\n",
        "\n",
        "# Download sample data\n",
        "bucket = \"ont-exd-int-s3-euwst1-epi2me-labs\"\n",
        "domain = \"s3-eu-west-1.amazonaws.com\"\n",
        "site = \"https://{}.{}\".format(bucket, domain)\n",
        "\n",
        "!wget \"$site/fast_introduction/archive.tar.gz\"\n",
        "!tar -xzvf archive.tar.gz\n",
        "%cd test0"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "T7R3ZA2GF6HT",
        "colab_type": "text"
      },
      "source": [
        "The snippets all have their code to the left-hand side and a form to the right which can be used to change their inputs (as an alternative to directly editing the code)."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Yu8wQ5mc-69P",
        "colab_type": "text"
      },
      "source": [
        "#### How many records in my `.fastq` file?\n",
        "\n",
        "To count the number of records in a `.fastq` file we can use the linux [word count](https://linux.die.net/man/1/wc) command to count the number of lines in a file, with a division by four accounting for four lines per record:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "f-e8UiQE8qyw",
        "colab_type": "code",
        "cellView": "both",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "cb4eb9d0-522f-4ff0-bb5a-ba3c34808cb2"
      },
      "source": [
        "filename = \"example3.fastq\"  #@param {type: \"string\"}\n",
        "!echo $(( $(wc -l < $filename) / 4 )) reads"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "100 reads\r\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "vOwokQTOIZ0N",
        "colab_type": "text"
      },
      "source": [
        "#### List all the fastqs in a directory\n",
        "\n",
        "As Oxford Nanopore Technologies' sequencing devices output multiple `.fastq` files during the course of an experiment, it can be useful to find and list all such files. We can do this with the linux [find](https://linux.die.net/man/1/find) command:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Toslxto7HgIn",
        "colab_type": "code",
        "cellView": "both",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 68
        },
        "outputId": "73dfdb07-b5b5-46ef-e264-f0598c5cc623"
      },
      "source": [
        "directory = \".\" #@param {type: \"string\"}\n",
        "\n",
        "!find $directory -name \"*.fastq\""
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "./example3.fastq\r\n",
            "./fail/example1.fastq\r\n",
            "./pass/example2.fastq\r\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zMt6_aeYsudk",
        "colab_type": "text"
      },
      "source": [
        "The default directory value here (`.`) means \"the current working directory.\""
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "huYtv1u3JDXn",
        "colab_type": "text"
      },
      "source": [
        "#### Concatenate all fastqs in a directory into a single file\n",
        "\n",
        "Many bioinformatics programs require all sequence data to be present in a single `.fastq` file. In order to process sequences across multiple files we must concatenate (or \"cat\") all the `.fastq` files into a single consolidated file. To perform this task we can use a combination of the linux [find](https://linux.die.net/man/1/find), [xargs](https://linux.die.net/man/1/xargs), and [cat](https://linux.die.net/man/1/cat) commands:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "F2kqVNt886Rd",
        "colab_type": "code",
        "cellView": "both",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "8736bbcc-1e37-477c-c63c-a2bfbcf94ac1"
      },
      "source": [
        "directory = \".\" #@param {type: \"string\"}\n",
        "output_fastq = \"all_records.fastq\" #@param {type: \"string\"}\n",
        "\n",
        "!find . -type f \\( -iname \"*.fastq\" ! -iname $output_fastq \\) | \\\n",
        "    xargs cat > $output_fastq\n",
        "!echo $(( $(wc -l < $output_fastq) / 4 )) reads"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "300 reads\r\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Ze2sQyDht1ol",
        "colab_type": "text"
      },
      "source": [
        "Again the default directory value here (`.`) means \"the current working directory.\"\n",
        "\n",
        "You may often see a simple form of the above:\n",
        "\n",
        "    cat *.fastq > output.fastq\n",
        "\n",
        "however, this command will fail if the number of `.fastq` files found is very large."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "SXx3keHyNPKS",
        "colab_type": "text"
      },
      "source": [
        "#### Remove all duplicates in a fastq\n",
        "\n",
        "In can sometimes be the case that for some reason a `.fastq` file contains duplicates of the same read. To remove these we can use the [`rmdup`](https://bioinf.shenwei.me/seqkit/usage/#rmdup) command of the [seqkit](https://github.com/shenwei356/seqkit) program:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dgl4TSS2NrB1",
        "colab_type": "code",
        "cellView": "both",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "d18767d0-135c-4445-d895-c2c11470530c"
      },
      "source": [
        "input_fastq = \"all_records.fastq\" #@param {type: \"string\"}\n",
        "output_fastq = \"deduplicated.fastq\" #@param {type: \"string\"}\n",
        "\n",
        "!seqkit rmdup \"$input_fastq\" -o \"$output_fastq\""
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[INFO]\u001b[0m 200 duplicated records removed\r\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "TJh81ziw4ltw",
        "colab_type": "text"
      },
      "source": [
        "For the example data, 200 duplicate records are identified because the three files (containing 100 records each) are in fact copies of the same file."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qPBWIDOcVE6L",
        "colab_type": "text"
      },
      "source": [
        "#### Compress or extract a fastq file\n",
        "\n",
        "We can save hard disk space on our computer by compressing `.fastq` files. To do this we recommend using [`bgzip`](http://www.htslib.org/doc/bgzip.html) which allows for indexing and fast retrieval of sequences by bioinformatics programs:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gzW6vTXMVKcr",
        "colab_type": "code",
        "cellView": "both",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "ad1fba84-16fb-4506-b083-caca45222aaa"
      },
      "source": [
        "input_fastq = \"example3.fastq\" #@param {type: \"string\"}\n",
        "compressed_fastq = \"example3.fastq.gz\" #@param {type: \"string\"}\n",
        "!ls -lh \"$input_fastq\"\n",
        "!bgzip \"$input_fastq\"\n",
        "!ls -lh \"$compressed_fastq\""
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "-rw-r--r-- 1 jovyan users 1.8M Apr 21 16:52 example3.fastq\n",
            "-rw-r--r-- 1 jovyan users 892K May 28 13:55 example3.fastq.gz\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ELqn2HOS2YdF",
        "colab_type": "text"
      },
      "source": [
        "The size of the compressed file is roughly half of the original. To decompress the compress file, we again use `bgzip`:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6MRicIUUWLPc",
        "colab_type": "code",
        "cellView": "both",
        "colab": {}
      },
      "source": [
        "compressed_fastq = \"example3.fastq.gz\" #@param {type: \"string\"}\n",
        "!bgzip -d \"$compressed_fastq\""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "IXvB3Kpq3MQJ",
        "colab_type": "text"
      },
      "source": [
        "#### Compress a directory structure\n",
        "\n",
        "In order to compress a directory structure we can use the linux [`tar`](https://linux.die.net/man/1/tar) command with the compression option: "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "J7cNxaaC3iAw",
        "colab_type": "code",
        "cellView": "both",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 51
        },
        "outputId": "0eb6430a-41ad-4893-9314-808450ec70a3"
      },
      "source": [
        "directory = \"pass\" #@param {type: \"string\"}\n",
        "archive = \"archive.tar.gz\" #@param {type: \"string\"}\n",
        "\n",
        "# the options here mean: create, gzip compress, verbose, output file\n",
        "!tar -czvf \"$archive\" \"$directory\""
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "pass/\r\n",
            "pass/example2.fastq\r\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3olXzFLP34Kd",
        "colab_type": "text"
      },
      "source": [
        "When compressing directories and their contents in this way it is good practice to compress a single top-level directory, so that when the archive is decompressed a single top-level directory is retrieved (and the users working directory isn't polluted).\n",
        "\n",
        "To decompress the archive we use a similar command:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nCZ_MzoE42pN",
        "colab_type": "code",
        "cellView": "both",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 51
        },
        "outputId": "e1b8d426-ad2f-4c26-d086-b6cc966d79c7"
      },
      "source": [
        "archive = \"archive.tar.gz\" #@param {type: \"string\"}\n",
        "\n",
        "# A temporary folder (tmp) is created here simply to avoid confusion with the\n",
        "# original directory compressed in the previous example. This is not necessary\n",
        "# in practice.\n",
        "\n",
        "# the options here mean: extract, gzip compressed, verbose, input file\n",
        "!rm -rf tmp && mkdir tmp && cd tmp && \\\n",
        "    tar -xzvf ../\"$archive\""
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "pass/\r\n",
            "pass/example2.fastq\r\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7XgSmykutHVY",
        "colab_type": "text"
      },
      "source": [
        "## Visualizing fastq\n",
        "\n",
        "The snippets below demonstrate basic parsing of fastq data in python. We do not recommend using this code in practice as much of the information is more readily available in the `sequencing_summary.txt` file produced by Oxford Nanopore Technologies' sequencing devices. See our [Basic QC Tutorial](https://colab.research.google.com/github/epi2me-labs/tutorials/blob/master/basic_qc_tutorial.ipynb) for more examples."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "eqTpLNMAtN5w",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 297
        },
        "outputId": "472c098c-051e-425e-9d4f-c7e8b45301d8"
      },
      "source": [
        "pinger.send_notebook_ping('stop', 'fastq_introduction')\n",
        "\n",
        "import numpy as np\n",
        "from pysam import FastxFile\n",
        "from bokeh.layouts import gridplot\n",
        "\n",
        "qualities = list()\n",
        "mean_qualities = list()\n",
        "lengths = list()\n",
        "\n",
        "# open the file and iterate through its records\n",
        "with FastxFile(\"all_records.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",
        "        # all qualities\n",
        "        qualities.extend(quals)\n",
        "        lengths.append(len(quals))\n",
        "\n",
        "# use the aplanat library to plot some graphs of the\n",
        "# collected statistics\n",
        "import aplanat\n",
        "from aplanat.hist import histogram\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",
        "    [qualities], title=\"Base quality scores\",\n",
        "    x_axis_label=\"quality\", y_axis_label=\"count\",\n",
        "    height=250, width=300)\n",
        "p3 = histogram(\n",
        "    [lengths], title=\"Read lengths\",\n",
        "    x_axis_label=\"read length / bases\", y_axis_label=\"count\",\n",
        "    height=250, width=300)\n",
        "aplanat.show(gridplot((p1, p2, p3), ncols=3))"
      ],
      "execution_count": null,
      "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",
              "  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=\"9569350b-3b3d-4afd-a391-f518bb8f214e\" data-root-id=\"1154\"></div>\n"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "application/javascript": [
              "(function(root) {\n",
              "  function embed_document(root) {\n",
              "    \n",
              "  var docs_json = {\"d4ce21bb-32ec-49ff-9bec-cd2e97f71f1d\":{\"roots\":{\"references\":[{\"attributes\":{\"children\":[{\"id\":\"1153\",\"type\":\"ToolbarBox\"},{\"id\":\"1151\",\"type\":\"GridBox\"}]},\"id\":\"1154\",\"type\":\"Column\"},{\"attributes\":{\"bottom\":{\"value\":0},\"fill_alpha\":{\"value\":0.1},\"fill_color\":{\"value\":\"#1f77b4\"},\"left\":{\"field\":\"left\"},\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"#1f77b4\"},\"right\":{\"field\":\"right\"},\"top\":{\"field\":\"top\"}},\"id\":\"1037\",\"type\":\"Quad\"},{\"attributes\":{\"ticker\":{\"id\":\"1095\",\"type\":\"BasicTicker\"}},\"id\":\"1098\",\"type\":\"Grid\"},{\"attributes\":{\"bounds\":[7.141442797955063,17.526228976201306],\"callback\":null,\"end\":17.526228976201306,\"start\":7.141442797955063},\"id\":\"1040\",\"type\":\"Range1d\"},{\"attributes\":{\"axis_label\":\"count\",\"formatter\":{\"id\":\"1143\",\"type\":\"BasicTickFormatter\"},\"ticker\":{\"id\":\"1100\",\"type\":\"BasicTicker\"}},\"id\":\"1099\",\"type\":\"LinearAxis\"},{\"attributes\":{},\"id\":\"1100\",\"type\":\"BasicTicker\"},{\"attributes\":{\"dimension\":1,\"ticker\":{\"id\":\"1100\",\"type\":\"BasicTicker\"}},\"id\":\"1103\",\"type\":\"Grid\"},{\"attributes\":{\"children\":[[{\"id\":\"1001\",\"subtype\":\"Figure\",\"type\":\"Plot\"},0,0],[{\"id\":\"1042\",\"subtype\":\"Figure\",\"type\":\"Plot\"},0,1],[{\"id\":\"1083\",\"subtype\":\"Figure\",\"type\":\"Plot\"},0,2]]},\"id\":\"1151\",\"type\":\"GridBox\"},{\"attributes\":{\"callback\":null,\"data\":{\"left\":{\"__ndarray__\":\"AAAAAADgY0As9zTCcl+gQFjuaYTlgK9AwnJPIyxRt0BY7mmE5eG+QPc0wnJPOcNAwnJPI6wBx0CNsNzTCMrKQFjuaYRlks5AEpZ7GmEt0UD3NMJyjxHTQNzTCMu99dRAwnJPI+zZ1kCoEZZ7Gr7YQI2w3NNIotpAck8jLHeG3EBY7mmEpWreQJ9GWO5pJ+BAEpZ7GoEZ4UCE5Z5GmAviQPc0wnKv/eJAaoTlnsbv40Dc0wjL3eHkQE8jLPf00+VAwnJPIwzG5kA1wnJPI7jnQKgRlns6quhAGmG5p1Gc6UCNsNzTaI7qQA==\",\"dtype\":\"float64\",\"shape\":[29]},\"right\":{\"__ndarray__\":\"LPc0wnJfoEBY7mmE5YCvQMJyTyMsUbdAWO5phOXhvkD3NMJyTznDQMJyTyOsAcdAjbDc0wjKykBY7mmEZZLOQBKWexphLdFA9zTCco8R00Dc0wjLvfXUQMJyTyPs2dZAqBGWexq+2ECNsNzTSKLaQHJPIyx3htxAWO5phKVq3kCfRljuaSfgQBKWexqBGeFAhOWeRpgL4kD3NMJyr/3iQGqE5Z7G7+NA3NMIy93h5EBPIyz39NPlQMJyTyMMxuZANcJyTyO450CoEZZ7OqroQBphuadRnOlAjbDc02iO6kAAAAAAgIDrQA==\",\"dtype\":\"float64\",\"shape\":[29]},\"top\":[93,51,42,18,18,12,12,6,0,6,6,3,6,0,0,0,3,3,6,3,0,0,6,0,3,0,0,0,3]},\"selected\":{\"id\":\"1148\",\"type\":\"Selection\"},\"selection_policy\":{\"id\":\"1149\",\"type\":\"UnionRenderers\"}},\"id\":\"1117\",\"type\":\"ColumnDataSource\"},{\"attributes\":{},\"id\":\"1127\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"active_drag\":\"auto\",\"active_inspect\":\"auto\",\"active_multi\":null,\"active_scroll\":\"auto\",\"active_tap\":\"auto\",\"tools\":[{\"id\":\"1104\",\"type\":\"PanTool\"},{\"id\":\"1105\",\"type\":\"WheelZoomTool\"},{\"id\":\"1106\",\"type\":\"BoxZoomTool\"},{\"id\":\"1107\",\"type\":\"SaveTool\"},{\"id\":\"1108\",\"type\":\"ResetTool\"},{\"id\":\"1109\",\"type\":\"HelpTool\"}]},\"id\":\"1110\",\"type\":\"Toolbar\"},{\"attributes\":{},\"id\":\"1104\",\"type\":\"PanTool\"},{\"attributes\":{},\"id\":\"1105\",\"type\":\"WheelZoomTool\"},{\"attributes\":{\"bounds\":[0,345537],\"callback\":null,\"end\":345537},\"id\":\"1082\",\"type\":\"Range1d\"},{\"attributes\":{\"overlay\":{\"id\":\"1147\",\"type\":\"BoxAnnotation\"}},\"id\":\"1106\",\"type\":\"BoxZoomTool\"},{\"attributes\":{},\"id\":\"1013\",\"type\":\"BasicTicker\"},{\"attributes\":{},\"id\":\"1107\",\"type\":\"SaveTool\"},{\"attributes\":{},\"id\":\"1108\",\"type\":\"ResetTool\"},{\"attributes\":{},\"id\":\"1109\",\"type\":\"HelpTool\"},{\"attributes\":{\"ticker\":{\"id\":\"1013\",\"type\":\"BasicTicker\"}},\"id\":\"1016\",\"type\":\"Grid\"},{\"attributes\":{\"bottom\":{\"value\":0},\"fill_alpha\":{\"value\":0.6},\"fill_color\":{\"value\":\"blue\"},\"left\":{\"field\":\"left\"},\"line_alpha\":{\"value\":0.6},\"line_color\":{\"value\":\"blue\"},\"right\":{\"field\":\"right\"},\"top\":{\"field\":\"top\"}},\"id\":\"1118\",\"type\":\"Quad\"},{\"attributes\":{\"bottom\":{\"value\":0},\"fill_alpha\":{\"value\":0.1},\"fill_color\":{\"value\":\"#1f77b4\"},\"left\":{\"field\":\"left\"},\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"#1f77b4\"},\"right\":{\"field\":\"right\"},\"top\":{\"field\":\"top\"}},\"id\":\"1119\",\"type\":\"Quad\"},{\"attributes\":{},\"id\":\"1027\",\"type\":\"HelpTool\"},{\"attributes\":{\"data_source\":{\"id\":\"1117\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"1118\",\"type\":\"Quad\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"1119\",\"type\":\"Quad\"},\"selection_glyph\":null,\"view\":{\"id\":\"1121\",\"type\":\"CDSView\"}},\"id\":\"1120\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"source\":{\"id\":\"1117\",\"type\":\"ColumnDataSource\"}},\"id\":\"1121\",\"type\":\"CDSView\"},{\"attributes\":{\"bottom_units\":\"screen\",\"fill_alpha\":{\"value\":0.5},\"fill_color\":{\"value\":\"lightgrey\"},\"left_units\":\"screen\",\"level\":\"overlay\",\"line_alpha\":{\"value\":1.0},\"line_color\":{\"value\":\"black\"},\"line_dash\":[4,4],\"line_width\":{\"value\":2},\"render_mode\":\"css\",\"right_units\":\"screen\",\"top_units\":\"screen\"},\"id\":\"1129\",\"type\":\"BoxAnnotation\"},{\"attributes\":{\"axis_label\":\"count\",\"formatter\":{\"id\":\"1125\",\"type\":\"BasicTickFormatter\"},\"ticker\":{\"id\":\"1018\",\"type\":\"BasicTicker\"}},\"id\":\"1017\",\"type\":\"LinearAxis\"},{\"attributes\":{},\"id\":\"1130\",\"type\":\"Selection\"},{\"attributes\":{},\"id\":\"1131\",\"type\":\"UnionRenderers\"},{\"attributes\":{},\"id\":\"1134\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{},\"id\":\"1136\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"bottom_units\":\"screen\",\"fill_alpha\":{\"value\":0.5},\"fill_color\":{\"value\":\"lightgrey\"},\"left_units\":\"screen\",\"level\":\"overlay\",\"line_alpha\":{\"value\":1.0},\"line_color\":{\"value\":\"black\"},\"line_dash\":[4,4],\"line_width\":{\"value\":2},\"render_mode\":\"css\",\"right_units\":\"screen\",\"top_units\":\"screen\"},\"id\":\"1138\",\"type\":\"BoxAnnotation\"},{\"attributes\":{\"bounds\":[0,42],\"callback\":null,\"end\":42},\"id\":\"1041\",\"type\":\"Range1d\"},{\"attributes\":{},\"id\":\"1139\",\"type\":\"Selection\"},{\"attributes\":{},\"id\":\"1140\",\"type\":\"UnionRenderers\"},{\"attributes\":{},\"id\":\"1143\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"below\":[{\"id\":\"1053\",\"type\":\"LinearAxis\"}],\"center\":[{\"id\":\"1057\",\"type\":\"Grid\"},{\"id\":\"1062\",\"type\":\"Grid\"}],\"left\":[{\"id\":\"1058\",\"type\":\"LinearAxis\"}],\"output_backend\":\"webgl\",\"plot_height\":250,\"plot_width\":300,\"renderers\":[{\"id\":\"1079\",\"type\":\"GlyphRenderer\"}],\"title\":{\"id\":\"1043\",\"type\":\"Title\"},\"toolbar\":{\"id\":\"1069\",\"type\":\"Toolbar\"},\"toolbar_location\":null,\"x_range\":{\"id\":\"1081\",\"type\":\"Range1d\"},\"x_scale\":{\"id\":\"1049\",\"type\":\"LinearScale\"},\"y_range\":{\"id\":\"1082\",\"type\":\"Range1d\"},\"y_scale\":{\"id\":\"1051\",\"type\":\"LinearScale\"}},\"id\":\"1042\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{},\"id\":\"1145\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"bottom_units\":\"screen\",\"fill_alpha\":{\"value\":0.5},\"fill_color\":{\"value\":\"lightgrey\"},\"left_units\":\"screen\",\"level\":\"overlay\",\"line_alpha\":{\"value\":1.0},\"line_color\":{\"value\":\"black\"},\"line_dash\":[4,4],\"line_width\":{\"value\":2},\"render_mode\":\"css\",\"right_units\":\"screen\",\"top_units\":\"screen\"},\"id\":\"1147\",\"type\":\"BoxAnnotation\"},{\"attributes\":{},\"id\":\"1148\",\"type\":\"Selection\"},{\"attributes\":{},\"id\":\"1149\",\"type\":\"UnionRenderers\"},{\"attributes\":{},\"id\":\"1008\",\"type\":\"LinearScale\"},{\"attributes\":{\"tools\":[{\"id\":\"1022\",\"type\":\"PanTool\"},{\"id\":\"1023\",\"type\":\"WheelZoomTool\"},{\"id\":\"1024\",\"type\":\"BoxZoomTool\"},{\"id\":\"1025\",\"type\":\"SaveTool\"},{\"id\":\"1026\",\"type\":\"ResetTool\"},{\"id\":\"1027\",\"type\":\"HelpTool\"},{\"id\":\"1063\",\"type\":\"PanTool\"},{\"id\":\"1064\",\"type\":\"WheelZoomTool\"},{\"id\":\"1065\",\"type\":\"BoxZoomTool\"},{\"id\":\"1066\",\"type\":\"SaveTool\"},{\"id\":\"1067\",\"type\":\"ResetTool\"},{\"id\":\"1068\",\"type\":\"HelpTool\"},{\"id\":\"1104\",\"type\":\"PanTool\"},{\"id\":\"1105\",\"type\":\"WheelZoomTool\"},{\"id\":\"1106\",\"type\":\"BoxZoomTool\"},{\"id\":\"1107\",\"type\":\"SaveTool\"},{\"id\":\"1108\",\"type\":\"ResetTool\"},{\"id\":\"1109\",\"type\":\"HelpTool\"}]},\"id\":\"1152\",\"type\":\"ProxyToolbar\"},{\"attributes\":{\"toolbar\":{\"id\":\"1152\",\"type\":\"ProxyToolbar\"},\"toolbar_location\":\"above\"},\"id\":\"1153\",\"type\":\"ToolbarBox\"},{\"attributes\":{\"below\":[{\"id\":\"1012\",\"type\":\"LinearAxis\"}],\"center\":[{\"id\":\"1016\",\"type\":\"Grid\"},{\"id\":\"1021\",\"type\":\"Grid\"}],\"left\":[{\"id\":\"1017\",\"type\":\"LinearAxis\"}],\"output_backend\":\"webgl\",\"plot_height\":250,\"plot_width\":300,\"renderers\":[{\"id\":\"1038\",\"type\":\"GlyphRenderer\"}],\"title\":{\"id\":\"1002\",\"type\":\"Title\"},\"toolbar\":{\"id\":\"1028\",\"type\":\"Toolbar\"},\"toolbar_location\":null,\"x_range\":{\"id\":\"1040\",\"type\":\"Range1d\"},\"x_scale\":{\"id\":\"1008\",\"type\":\"LinearScale\"},\"y_range\":{\"id\":\"1041\",\"type\":\"Range1d\"},\"y_scale\":{\"id\":\"1010\",\"type\":\"LinearScale\"}},\"id\":\"1001\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{},\"id\":\"1010\",\"type\":\"LinearScale\"},{\"attributes\":{\"active_drag\":\"auto\",\"active_inspect\":\"auto\",\"active_multi\":null,\"active_scroll\":\"auto\",\"active_tap\":\"auto\",\"tools\":[{\"id\":\"1022\",\"type\":\"PanTool\"},{\"id\":\"1023\",\"type\":\"WheelZoomTool\"},{\"id\":\"1024\",\"type\":\"BoxZoomTool\"},{\"id\":\"1025\",\"type\":\"SaveTool\"},{\"id\":\"1026\",\"type\":\"ResetTool\"},{\"id\":\"1027\",\"type\":\"HelpTool\"}]},\"id\":\"1028\",\"type\":\"Toolbar\"},{\"attributes\":{\"source\":{\"id\":\"1035\",\"type\":\"ColumnDataSource\"}},\"id\":\"1039\",\"type\":\"CDSView\"},{\"attributes\":{\"axis_label\":\"quality\",\"formatter\":{\"id\":\"1127\",\"type\":\"BasicTickFormatter\"},\"ticker\":{\"id\":\"1013\",\"type\":\"BasicTicker\"}},\"id\":\"1012\",\"type\":\"LinearAxis\"},{\"attributes\":{\"bounds\":[159,56324],\"callback\":null,\"end\":56324,\"start\":159},\"id\":\"1122\",\"type\":\"Range1d\"},{\"attributes\":{},\"id\":\"1049\",\"type\":\"LinearScale\"},{\"attributes\":{},\"id\":\"1051\",\"type\":\"LinearScale\"},{\"attributes\":{\"axis_label\":\"quality\",\"formatter\":{\"id\":\"1136\",\"type\":\"BasicTickFormatter\"},\"ticker\":{\"id\":\"1054\",\"type\":\"BasicTicker\"}},\"id\":\"1053\",\"type\":\"LinearAxis\"},{\"attributes\":{},\"id\":\"1054\",\"type\":\"BasicTicker\"},{\"attributes\":{\"ticker\":{\"id\":\"1054\",\"type\":\"BasicTicker\"}},\"id\":\"1057\",\"type\":\"Grid\"},{\"attributes\":{\"data_source\":{\"id\":\"1035\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"1036\",\"type\":\"Quad\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"1037\",\"type\":\"Quad\"},\"selection_glyph\":null,\"view\":{\"id\":\"1039\",\"type\":\"CDSView\"}},\"id\":\"1038\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"axis_label\":\"count\",\"formatter\":{\"id\":\"1134\",\"type\":\"BasicTickFormatter\"},\"ticker\":{\"id\":\"1059\",\"type\":\"BasicTicker\"}},\"id\":\"1058\",\"type\":\"LinearAxis\"},{\"attributes\":{},\"id\":\"1059\",\"type\":\"BasicTicker\"},{\"attributes\":{\"dimension\":1,\"ticker\":{\"id\":\"1059\",\"type\":\"BasicTicker\"}},\"id\":\"1062\",\"type\":\"Grid\"},{\"attributes\":{\"callback\":null,\"data\":{\"left\":{\"__ndarray__\":\"AAAAAAAA8D/uaYTlnkYQQN3TCMs9jRxA5p5GWO5pJEDd0wjLPY0qQGqE5Z5GWDBA5p5GWO5pM0BhuacRlns2QN3TCMs9jTlAWe5phOWePEDUCMs9jbA/QKgRlnsaYUFA5p5GWO7pQkAkLPc0wnJEQGG5pxGW+0VAn0ZY7mmER0Dd0wjLPQ1JQBthuacRlkpAWe5phOUeTECWexphuadNQNQIyz2NME9ACcs9jbBcUECoEZZ7GiFRQEdY7mmE5VFA5p5GWO6pUkCF5Z5GWG5TQCQs9zTCMlRAwnJPIyz3VEBhuacRlrtVQA==\",\"dtype\":\"float64\",\"shape\":[29]},\"right\":{\"__ndarray__\":\"7mmE5Z5GEEDd0wjLPY0cQOaeRljuaSRA3dMIyz2NKkBqhOWeRlgwQOaeRljuaTNAYbmnEZZ7NkDd0wjLPY05QFnuaYTlnjxA1AjLPY2wP0CoEZZ7GmFBQOaeRlju6UJAJCz3NMJyREBhuacRlvtFQJ9GWO5phEdA3dMIyz0NSUAbYbmnEZZKQFnuaYTlHkxAlnsaYbmnTUDUCMs9jTBPQAnLPY2wXFBAqBGWexohUUBHWO5phOVRQOaeRljuqVJAheWeRlhuU0AkLPc0wjJUQMJyTyMs91RAYbmnEZa7VUAAAAAAAIBWQA==\",\"dtype\":\"float64\",\"shape\":[29]},\"top\":[97830,132732,132726,145080,162981,190569,232008,285726,335409,345537,282138,175311,85530,35277,15102,2979,1116,384,213,54,24,15,0,0,0,0,0,0,6]},\"selected\":{\"id\":\"1139\",\"type\":\"Selection\"},\"selection_policy\":{\"id\":\"1140\",\"type\":\"UnionRenderers\"}},\"id\":\"1076\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"text\":\"Read lengths\"},\"id\":\"1084\",\"type\":\"Title\"},{\"attributes\":{\"text\":\"Read quality scores\"},\"id\":\"1002\",\"type\":\"Title\"},{\"attributes\":{\"below\":[{\"id\":\"1094\",\"type\":\"LinearAxis\"}],\"center\":[{\"id\":\"1098\",\"type\":\"Grid\"},{\"id\":\"1103\",\"type\":\"Grid\"}],\"left\":[{\"id\":\"1099\",\"type\":\"LinearAxis\"}],\"output_backend\":\"webgl\",\"plot_height\":250,\"plot_width\":300,\"renderers\":[{\"id\":\"1120\",\"type\":\"GlyphRenderer\"}],\"title\":{\"id\":\"1084\",\"type\":\"Title\"},\"toolbar\":{\"id\":\"1110\",\"type\":\"Toolbar\"},\"toolbar_location\":null,\"x_range\":{\"id\":\"1122\",\"type\":\"Range1d\"},\"x_scale\":{\"id\":\"1090\",\"type\":\"LinearScale\"},\"y_range\":{\"id\":\"1123\",\"type\":\"Range1d\"},\"y_scale\":{\"id\":\"1092\",\"type\":\"LinearScale\"}},\"id\":\"1083\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{\"active_drag\":\"auto\",\"active_inspect\":\"auto\",\"active_multi\":null,\"active_scroll\":\"auto\",\"active_tap\":\"auto\",\"tools\":[{\"id\":\"1063\",\"type\":\"PanTool\"},{\"id\":\"1064\",\"type\":\"WheelZoomTool\"},{\"id\":\"1065\",\"type\":\"BoxZoomTool\"},{\"id\":\"1066\",\"type\":\"SaveTool\"},{\"id\":\"1067\",\"type\":\"ResetTool\"},{\"id\":\"1068\",\"type\":\"HelpTool\"}]},\"id\":\"1069\",\"type\":\"Toolbar\"},{\"attributes\":{},\"id\":\"1063\",\"type\":\"PanTool\"},{\"attributes\":{},\"id\":\"1064\",\"type\":\"WheelZoomTool\"},{\"attributes\":{\"overlay\":{\"id\":\"1138\",\"type\":\"BoxAnnotation\"}},\"id\":\"1065\",\"type\":\"BoxZoomTool\"},{\"attributes\":{},\"id\":\"1066\",\"type\":\"SaveTool\"},{\"attributes\":{},\"id\":\"1067\",\"type\":\"ResetTool\"},{\"attributes\":{},\"id\":\"1068\",\"type\":\"HelpTool\"},{\"attributes\":{},\"id\":\"1018\",\"type\":\"BasicTicker\"},{\"attributes\":{\"bottom\":{\"value\":0},\"fill_alpha\":{\"value\":0.6},\"fill_color\":{\"value\":\"blue\"},\"left\":{\"field\":\"left\"},\"line_alpha\":{\"value\":0.6},\"line_color\":{\"value\":\"blue\"},\"right\":{\"field\":\"right\"},\"top\":{\"field\":\"top\"}},\"id\":\"1077\",\"type\":\"Quad\"},{\"attributes\":{\"dimension\":1,\"ticker\":{\"id\":\"1018\",\"type\":\"BasicTicker\"}},\"id\":\"1021\",\"type\":\"Grid\"},{\"attributes\":{\"bottom\":{\"value\":0},\"fill_alpha\":{\"value\":0.1},\"fill_color\":{\"value\":\"#1f77b4\"},\"left\":{\"field\":\"left\"},\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"#1f77b4\"},\"right\":{\"field\":\"right\"},\"top\":{\"field\":\"top\"}},\"id\":\"1078\",\"type\":\"Quad\"},{\"attributes\":{\"data_source\":{\"id\":\"1076\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"1077\",\"type\":\"Quad\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"1078\",\"type\":\"Quad\"},\"selection_glyph\":null,\"view\":{\"id\":\"1080\",\"type\":\"CDSView\"}},\"id\":\"1079\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"text\":\"Base quality scores\"},\"id\":\"1043\",\"type\":\"Title\"},{\"attributes\":{\"bounds\":[1,90],\"callback\":null,\"end\":90,\"start\":1},\"id\":\"1081\",\"type\":\"Range1d\"},{\"attributes\":{\"source\":{\"id\":\"1076\",\"type\":\"ColumnDataSource\"}},\"id\":\"1080\",\"type\":\"CDSView\"},{\"attributes\":{\"callback\":null,\"data\":{\"left\":{\"__ndarray__\":\"DuN9YdaQHEAonUseh/8dQEJXGds3bh9ArojzS3RuIEC7ZVqqzCUhQMhCwQgl3SFA1B8oZ32UIkDi/I7F1UsjQO7Z9SMuAyRA/LZcgoa6JEAIlMPg3nElQBVxKj83KSZAIk6RnY/gJkAvK/j755cnQDwIX1pATyhASeXFuJgGKUBWwiwX8b0pQGOfk3VJdSpAcHz606EsK0B9WWEy+uMrQIo2yJBSmyxAlhMv76pSLUCk8JVNAwouQLHN/KtbwS5AvapjCrR4L0DlQ2U0BhgwQGyymGOyczBA8iDMkl7PMEB4j//BCisxQA==\",\"dtype\":\"float64\",\"shape\":[29]},\"right\":{\"__ndarray__\":\"KJ1LHof/HUBCVxnbN24fQK6I80t0biBAu2VaqswlIUDIQsEIJd0hQNQfKGd9lCJA4vyOxdVLI0Du2fUjLgMkQPy2XIKGuiRACJTD4N5xJUAVcSo/NykmQCJOkZ2P4CZALyv4++eXJ0A8CF9aQE8oQEnlxbiYBilAVsIsF/G9KUBjn5N1SXUqQHB8+tOhLCtAfVlhMvrjK0CKNsiQUpssQJYTL++qUi1ApPCVTQMKLkCxzfyrW8EuQL2qYwq0eC9A5UNlNAYYMEBssphjsnMwQPIgzJJezzBAeI//wQorMUD//TLxtoYxQA==\",\"dtype\":\"float64\",\"shape\":[29]},\"top\":[3,0,0,0,0,3,3,6,0,12,3,3,3,15,6,12,21,33,42,21,30,30,18,18,9,3,3,0,3]},\"selected\":{\"id\":\"1130\",\"type\":\"Selection\"},\"selection_policy\":{\"id\":\"1131\",\"type\":\"UnionRenderers\"}},\"id\":\"1035\",\"type\":\"ColumnDataSource\"},{\"attributes\":{},\"id\":\"1022\",\"type\":\"PanTool\"},{\"attributes\":{\"bounds\":[0,93],\"callback\":null,\"end\":93},\"id\":\"1123\",\"type\":\"Range1d\"},{\"attributes\":{\"bottom\":{\"value\":0},\"fill_alpha\":{\"value\":0.6},\"fill_color\":{\"value\":\"blue\"},\"left\":{\"field\":\"left\"},\"line_alpha\":{\"value\":0.6},\"line_color\":{\"value\":\"blue\"},\"right\":{\"field\":\"right\"},\"top\":{\"field\":\"top\"}},\"id\":\"1036\",\"type\":\"Quad\"},{\"attributes\":{},\"id\":\"1023\",\"type\":\"WheelZoomTool\"},{\"attributes\":{},\"id\":\"1125\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"overlay\":{\"id\":\"1129\",\"type\":\"BoxAnnotation\"}},\"id\":\"1024\",\"type\":\"BoxZoomTool\"},{\"attributes\":{},\"id\":\"1090\",\"type\":\"LinearScale\"},{\"attributes\":{},\"id\":\"1025\",\"type\":\"SaveTool\"},{\"attributes\":{},\"id\":\"1092\",\"type\":\"LinearScale\"},{\"attributes\":{},\"id\":\"1026\",\"type\":\"ResetTool\"},{\"attributes\":{\"axis_label\":\"read length / bases\",\"formatter\":{\"id\":\"1145\",\"type\":\"BasicTickFormatter\"},\"ticker\":{\"id\":\"1095\",\"type\":\"BasicTicker\"}},\"id\":\"1094\",\"type\":\"LinearAxis\"},{\"attributes\":{},\"id\":\"1095\",\"type\":\"BasicTicker\"}],\"root_ids\":[\"1154\"]},\"title\":\"Bokeh Application\",\"version\":\"1.4.0\"}};\n",
              "  var render_items = [{\"docid\":\"d4ce21bb-32ec-49ff-9bec-cd2e97f71f1d\",\"roots\":{\"1154\":\"9569350b-3b3d-4afd-a391-f518bb8f214e\"}}];\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": "1154"
            }
          }
        }
      ]
    }
  ]
}