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From RAPIDRUN FASTQ to OTU table

You can browse the different steps using the sidebar on the right.

Installation

Prerequisites

Installation via Conda

The default conda solver is a bit slow and sometimes has issues with selecting the latest package releases. Therefore, we recommend to install Mamba as a drop-in replacement via

conda install -c conda-forge mamba

Then, you can install Snakemake, pandas, biopython and dependencies with

mamba create -n snakemake_rapidrun -c conda-forge -c bioconda snakemake biopython pandas

from the conda-forge and bioconda channels. This will install all required software into an isolated software environment, that has to be activated with

conda activate snakemake_rapidrun

Get started

  • open a shell
  • clone the project and switch to the main folder, it's your working directory
git clone https://gitlab.mbb.univ-montp2.fr/edna/snakemake_rapidrun_swarm
cd snakemake_rapidrun_swarm
  • Activate the conda environment to access the required dependencies
conda activate snakemake_rapidrun

You are ready to run the analysis !

Download example data

curl -JLO http://gitlab.mbb.univ-montp2.fr/edna/snakemake_rapidrun_data_test/-/raw/master/test_rapidrun_data.tar.gz; tar zfxz test_rapidrun_data.tar.gz -C resources/test/
  • Data is downloaded at resources/test/test_rapidrun_data
  • this folder contains a reference database for 4 markers (Teleo01; Mamm01; Vert01; Chond01), NGS metabarcoding raw data, required metadata to handle demultiplexing on RAPIDRUN format

Run the workflow

Simply type the following command to process example data

snakemake --configfile config/config_test_rapidrun.yaml --cores 4 --use-conda
  • The first argument --configfile config/config_test_rapidrun.yaml contains parameters to apply
  • The second argument --cores 4 is the number of CPU cores you want to allow the system uses to run the whole workflow
  • The third argument --use-conda is only necessary if you installed the program and its dependencies using conda

Cluster MBB

clone the workflow

git clone https://gitlab.mbb.univ-montp2.fr/edna/snakemake_rapidrun_swarm.git
cd snakemake_rapidrun_obitools

Download data test (resources/test)

scp -r resources/test/ peguerin@162.38.181.66:~/snakemake_rapidrun_swarm/resources

Download singularity image (sedna.simg)

scp -r sedna.simg peguerin@162.38.181.66:~/snakemake_rapidrun_swarm/

load singularity module

module load singularity/3.5.3

run the workflow local

singularity exec sedna.simg snakemake --use-conda --configfile config/config_test_rapidrun.yaml -j 4

run the workflow sge

singularity exec sedna.simg snakemake --use-conda --cluster '/opt/gridengine/bin/linux-x64/qsub -q cemeb20.q -N testsmk -j y -pe robin 16' --configfile config/config_test_rapidrun.yaml -j 16