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Commit 2ed95d57 authored by Helene Rimbert's avatar Helene Rimbert
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Merge branch 'helene.rimbert-master-patch-73205' into 'master'

Update README.md

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1 merge request!2Update README.md
......@@ -10,17 +10,28 @@ $ git clone git@forgemia.inra.fr:umr-gdec/magatt.git
## Dependancies
### Snakemake
* Version 5.5.2
### Build magatt environment with conda
### Python3
We recommend to build the environment using conda (developped with miniconda 3, conda 4.9.2 ) with the file [environment.yml](environment.yml):
```console
$ conda env create -f=environment.yml -n magatt
```
Once created, you can activate the environment with:
```console
$ conda activate magatt
```
All the dependancies are listed below.
* Snakemake : 5.5.2
* Python: 3.5
* Biopython: 1.68
* numpy: 1.15
* pandas: 0.23
* pysam: 0.15
### Genomic Tools
* Bedtools: 2.27
* Blat: 36
* Exonerate (fastavalidcds): 2.4.0
......@@ -30,9 +41,9 @@ $ git clone git@forgemia.inra.fr:umr-gdec/magatt.git
* NCBI-blast (BLAST+): 2.6
* Samtools: 1.9
## Prepare the pipeline
## Prepare and run the pipeline
### Creating the configuration file
### Creating the configuration file: inputs and other parameters
The configuration file [config.yaml](config.yaml) will contain all the input files required for the pipeline and some other parameters.
......@@ -170,6 +181,11 @@ $ snakemake -j 32 --cluster sbatch
This will allow to have at most 32 subproccess run through the SLURM scheduler with `sbatch`.
You can use a custom [cluster.json](cluster.json) JSON file do setup the parameters of SBATCH for each rules, and use it with with:
```console
$ snakemake -j 32 -u cluster.json --cluster "sbatch -J {cluster.jobName} -c {cluster.c} --mem {cluster.mem} -e {cluster.error} -o {cluster.output} -p debug" --verbose"
```
You can generate the diagram of all the processes and dependancies of you analysis:
```bash
$ snakemake --dag |dot -T png > dag.png
......
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