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MetaCompore v0.1.3

Snakemake DOI


Metacompore is a snakemake pipeline running multiple RNA modifications detection tools for nanopore directRNA sequencing

At the moment MetaCompore supports the following tools:

Authors

  • Adrien Leger (@a-slide)
  • Tommaso Leonardi (@tleonardi)

Usage

Step 1: Obtain a copy of this workflow

Clone the last tarball archive of the pipeline to your local system, into the location where you want to perform the data analysis

wget https://github.com/a-slide/MetaCompore/releases/download/0.1.3/MetaCompore.tar.gz
tar xzf MetaCompore.tar.gz
cd MetaCompore

Step 2: Install dependencies

Singularity

If required, install singularity following the official documentation: https://sylabs.io/guides/3.7/user-guide/quick_start.html

Conda / Mamba

Install miniconda following the official documentation: https://docs.conda.io/en/latest/miniconda.html

you can also install mamba to speed up snakemake installation: https://github.com/mamba-org/mamba

Snakemake

Create a virtual environment containing snakemake with conda

conda env create -f environment.yaml

You can also use mamba which will give you the same result, but much faster

mamba env create -f environment.yaml

Step 3: Configure the workflow

Configure the workflow according to your needs by editing the files config.yaml to configure the workflow execution

nano config.yaml

Edit the samples.tsv to specify your sample setup and fast5 source files

nano samples.tsv

Step 4: Execute workflow

Local Mode

Activate the conda environment:

conda activate snakemake
snakemake --use-singularity -j 4

LSF cluster Mode

Set an LSF cluster profile https://github.com/Snakemake-Profiles/lsf

Edit the lsf rule specific config file lsf.yaml

Disclaimer

Please be aware that MetaCompore is a research package that is still under development.

It was tested under Linux Ubuntu 16.04 and in an HPC environment running under Red Hat Enterprise 7.1.

Thank you

citation

Adrien Leger & Tommaso Leonardi. (2021, April 28). MetaCompore. Zenodo. http://doi.org/10.5281/zenodo.4726171

licence

MIT (https://mit-license.org/)

Copyright © 2020 Adrien Leger

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