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Unverified Commit 32674a28 authored by Laurent Modolo's avatar Laurent Modolo
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Merge branch 'master' of gitlab_lbmc:Delattre/JU28_59vs17_SNP

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# nextflow pipeline # SNP calling pipeline
This repository is a template and a library repository to help you build nextflow pipeline. SNP calling pipeline to find homozygote SNPs present in JU2817 strain but not in JU2859
You can fork this repository to build your own pipeline.
To get the last commits from this repository into your fork use the following commands:
```sh
git remote add upstream gitlab_lbmc:pipelines/nextflow.git
git pull upstream master
```
## Getting Started ## Getting Started
These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system. These instructions will get you a working version of the pipeline the SNP calling pipeline.
### Prerequisites ### Prerequisites
...@@ -35,75 +28,34 @@ To install nextflow on you computer simply run the following command: ...@@ -35,75 +28,34 @@ To install nextflow on you computer simply run the following command:
src/install_nextflow.sh src/install_nextflow.sh
``` ```
Then to initialize a given tools run the following command: Then to initialize the necessary Docker tools with the following command:
```sh
src/docker_modules/<tool_name>/<tool_version>/docker_init.sh
```
For example to initialize `file_handle` version `0.1.1`, run:
```sh
src/docker_modules/file_handle/0.1.1/docker_init.sh
```
To initialize all the tools:
```sh
find src/docker_modules/ -name "docker_init.sh" | awk '{system($0)}'
```
## Running the tests
To run tests we first need to get a training set
```sh ```sh
cd data src/docker_modules/cutadapt/1.14/docker_init.sh
git clone -c http.sslVerify=false https://gitlab.biologie.ens-lyon.fr/LBMC/tiny_dataset.git src/docker_modules/UrQt/d62c1f8/docker_init.sh
cp tiny_dataset/fastq/tiny_R1.fastq tiny_dataset/fastq/tiny2_R1.fastq src/docker_modules/bioawk/1.0/docker_init.sh
cp tiny_dataset/fastq/tiny_R2.fastq tiny_dataset/fastq/tiny2_R2.fastq src/docker_modules/Bowtie2/2.3.4.1/docker_init.sh
cp tiny_dataset/fastq/tiny_S.fastq tiny_dataset/fastq/tiny2_S.fastq src/docker_modules/sambamba/0.6.7/docker_init.sh
cd .. src/docker_modules/sambamba/0.6.7/docker_init.sh
src/docker_modules/GATK/4.0.8.1/docker_init.sh
src/docker_modules/SAMtools/1.7/docker_init.sh
src/docker_modules/bcftools/1.7/docker_init.sh
``` ```
Then to run the tests for a given tools run the following command: Necessary R packages
```sh ```sh
src/nf_modules/<tool_name>/<tool_version>/tests.sh R -e 'install.packages(c("tidyverse", "seqinr"), repos = "https://cloud.r-project.org")'
``` ```
For example to run the tests on `Bowtie2` run:
```sh ### Running
src/nf_modules/Bowtie2/tests.sh
```
## Available tools To launch the analysis, you can execute the content of the script `src/1_JU28_59vs17_SNP_calling.sh`.
There, is a first section to run the pipeline locally with Docker on a training set (after generating the training set), a second to run it with Docker on the full data set, and a last seciton to run it on the PSMN.
| tool | nf module | docker module | sge module |
|------|:---------:|:-------------:|:----------:|
BEDtools | ok | ok | ok
Bowtie | ok | ok | **no**
Bowtie2 | ok | ok | ok
canu | ok | ok | ok
cutadapt | ok | ok | ok
deepTools | **no** | ok | ok
FastQC | ok | ok | ok
file_handle | **no** | ok | ok
HISAT2 | **no** | ok | **no**
HTSeq | ok | ok | ok
Kallisto | ok | ok | ok
MACS2 | **no** | ok | ok
MultiQC | ok | ok | ok
MUSIC | ok | ok | ok
picard | **no** | ok | ok
pigz | **no** | ok | ok
RSEM | ok | ok | ok
SAMtools | ok | ok | ok
SRAtoolkit | ok | ok | ok
Salmon | **no** | ok | ok
TopHat | **no** | ok | ok
Trimmomatic | **no** | ok | ok
UrQt | ok | ok | ok
After running the `src/SNP_calling.nf` pipeline, the `src/intersect_SNP.R` R scripts will format the `.vcf` files into `.csv` table.
The final output is filtered to keep only SNP matching a list of enzymes and SNP that are homozygote in one strain and not present in the other.
## Contributing ## Contributing
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