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terrimporter authored May 10, 2021
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Expand Up @@ -49,7 +49,7 @@ If you use this dataflow or any of the provided scripts, please cite the MetaWor
Porter, T.M., Hajibabaei, M. 2020. METAWORKS: A flexible, scalable bioinformatic pipeline for multi-marker biodiversity assessments. BioRxiv, doi: https://doi.org/10.1101/2020.07.14.202960.

You can also site this repository:
Teresita M. Porter. (2020, June 25). MetaWorks: A Multi-Marker Metabarcode Pipeline (Version v1.6.1). Zenodo. http://doi.org/10.5281/zenodo.4741407
Teresita M. Porter. (2020, June 25). MetaWorks: A Multi-Marker Metabarcode Pipeline (Version v1.6.2). Zenodo. http://doi.org/10.5281/zenodo.4741407

If you use this dataflow for making COI taxonomic assignments, please cite the COI classifier publication:
Porter, T. M., & Hajibabaei, M. (2018). Automated high throughput animal CO1 metabarcode classification. Scientific Reports, 8, 4226.
Expand All @@ -76,7 +76,7 @@ Wang, Q., Garrity, G. M., Tiedje, J. M., & Cole, J. R. (2007). Naive Bayesian Cl

## Overview

MetaWorks comes with a conda environment file MetaWorks_v1.6.1 that should be activated before running the pipeline. Conda is an environment and package manager (Anaconda, 2016). The environment file contains most of the programs and dependencies needed to run MetaWorks. If pseudogene filtering will be used, then the NCBI ORFfinder program will also need to be installed. Additional RDP-trained reference sets may need to be downloaded if the reference set needed is not already built in to the RDP classifier (see Table 1 below).
MetaWorks comes with a conda environment file MetaWorks_v1.6.2 that should be activated before running the pipeline. Conda is an environment and package manager (Anaconda, 2016). The environment file contains most of the programs and dependencies needed to run MetaWorks. If pseudogene filtering will be used, then the NCBI ORFfinder program will also need to be installed. Additional RDP-trained reference sets may need to be downloaded if the reference set needed is not already built in to the RDP classifier (see Table 1 below).

Snakemake is a python-based workflow manager (Koster and Rahmann, 2012) and it requires three sets of files to run (Fig 1).

Expand Down Expand Up @@ -163,10 +163,10 @@ The final output file is results.csv and it has been formatted to specify ESVs f
conda env create -f environment.yml
# Activate the environment
conda activate MetaWorks_v1.6.1
conda activate MetaWorks_v1.6.2
# On the GPSC activate using source
source ~/miniconda/bin/activate MetaWorks_v1.6.1
source ~/miniconda/bin/activate MetaWorks_v1.6.2
```

2. The RDP classifier comes with the training sets to classify 16S, fungal LSU or ITS rDNA. To classify other markers using custom-trained RDP sets, obtain these from GitHub using Table 1 as a guide . Take note of where the rRNAclassifier.properties file is as this needs to be added to the config.yaml .
Expand All @@ -191,7 +191,7 @@ gunzip ORFfinder.gz
chmod a+x ORFfinder
# put in your conda environment bin
mv ORFfinder ~/miniconda3/envs/MetaWorks_v1.6.1/bin/.
mv ORFfinder ~/miniconda3/envs/MetaWorks_v1.6.2/bin/.
```

Run the program to test that it works:
Expand Down Expand Up @@ -243,10 +243,10 @@ cd ~/bin
ln -s ~/miniconda3/bin/conda conda
# Activate conda method 1 (working in a container)
source ~/miniconda3/bin/activate MetaWorks_v1.6.1
source ~/miniconda3/bin/activate MetaWorks_v1.6.2
# Activate conda method 2
conda activate MetaWorks_v1.6.1
conda activate MetaWorks_v1.6.2
```

### Checking program versions
Expand All @@ -258,7 +258,7 @@ Ensure the program versions in the environment are being used.
conda env create -f environment.yml
# activate the environment
conda activate MetaWorks_v1.6.1
conda activate MetaWorks_v1.6.2
# list all programs available in the environment at once
conda list > programs.list
Expand All @@ -283,11 +283,11 @@ If you have an older version of GLIBC, then you may be missing libraries that OR
Create a symbolic link to the library:

```linux
cd ~/miniconda3/envs/MetaWorks_v1.6.1/lib
cd ~/miniconda3/envs/MetaWorks_v1.6.2/lib
ln -s ../glibc-2.14/lib/libc.so.6 libc.so.6
```

Create the shell script file LD_PATH.sh in the following location to set the environment variable: ~/miniconda3/envs/MetaWorks_v1.6.1/etc/conda/activate.d/LD_PATH.sh
Create the shell script file LD_PATH.sh in the following location to set the environment variable: ~/miniconda3/envs/MetaWorks_v1.6.2/etc/conda/activate.d/LD_PATH.sh

Put the following text in the LD_PATH.sh file:

Expand All @@ -297,7 +297,7 @@ export LD_LIBRARY_PATH=$CONDA_PREFIX/lib:$LD_LIBRARY_PATH
```

Create the file LD_PATH.sh in the following location to unset the environment variable:
~/miniconda3/envs/MetaWorks_v1.6.1/etc/conda/deactivate.d/LD_PATH.sh
~/miniconda3/envs/MetaWorks_v1.6.2/etc/conda/deactivate.d/LD_PATH.sh

Put the following text in the LD_PATH.sh file:

Expand Down Expand Up @@ -351,7 +351,7 @@ nohup snakemake --jobs 24 --snakefile snakefile --configfile config.yaml
# to start a screen session
screen
ctrl+a+c
conda activate MetaWorks_v1.6.1
conda activate MetaWorks_v1.6.2
snakemake --jobs 24 --snakefile snakefile --configfile config.yaml
ctrl+a+d
Expand All @@ -370,14 +370,14 @@ We have provided a small set of COI paired-end Illumina MiSeq files for this tut

**Step 1. Prepare your environment for the pipeline.**

Begin by downloading the latest MetaWorks release available at https://github.com/terrimporter/MetaWorks/releases/tag/v1.6.1 by using wget from the command line:
Begin by downloading the latest MetaWorks release available at https://github.com/terrimporter/MetaWorks/releases/tag/v1.6.2 by using wget from the command line:

```linux
# download the pipeline
wget https://github.com/terrimporter/MetaWorks/releases/download/v1.6.1/MetaWorks1.6.1.tar.gz
wget https://github.com/terrimporter/MetaWorks/releases/download/v1.6.2/MetaWorks1.6.2.tar.gz
# unzip the pipeline
unzip MetaWorks1.6.1.zip
unzip MetaWorks1.6.2.zip
```

If you don't already have conda on your system, then you will need to install it:
Expand All @@ -400,17 +400,17 @@ cd ~/bin
ln -s ~/miniconda3/bin/conda conda
```

Create then activate the MetaWorks_v1.6.1 environment:
Create then activate the MetaWorks_v1.6.2 environment:

```linux
# Move into the MetaWorks folder
cd MetaWorks1.6.1
cd MetaWorks1.6.2
# Create the environment from the provided environment.yml file . Only need to do this step once.
conda env create -f environment.yml
# Activate the environment. Do this everytime before running the pipeline.
conda activate MetaWorks_v1.6.1
conda activate MetaWorks_v1.6.2
```

Expand Down

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