A repo for the Dockerfile to create a Docker image for the fastqc command. Also contains the
Dockstore.cwl which is used by the Dockstore to register
this container and describe how to call fastqc for the community.
This tool has been validated as a CWL v1.0 CommandLineTool.
Normally you would let Quay.io build this. But, if you need to build manually you would execute:
docker build -t quay.io/briandoconnor/fastqc:0.11.5 .
# get some NA12878 fastq data
$ wget ftp://ftp-trace.ncbi.nlm.nih.gov/giab/ftp/data/NA12878/NIST_NA12878_HG001_HiSeq_300x/140313_D00360_0014_AH8GGVADXX/Project_RM8398/Sample_U0b/U0b_TGACCA_L002_R1_006.fastq.gz
$ docker run -it -v `pwd`/U0b_TGACCA_L002_R1_006.fastq.gz:/U0b_TGACCA_L002_R1_006.fastq.gz quay.io/briandoconnor/fastqc:0.11.5 /bin/bash
# within the docker container
$ /usr/local/bin/run-fastqc --outdir . --fastq /U0b_TGACCA_L002_R1_006.fastq.gz
You should see an html and zip output.
This tool can be found at the Dockstore, login with your GitHub account and follow the directions to setup the CLI. It lets you run a Docker container with a CWL descriptor locally, using Docker and the CWL command line utility. This is great for testing.
This is the parameterization of the BAM stat tool, a copy is present in this repo called fastqc.json:
{
"fastq_files": [
{
"class": "File",
"path": "https://github.com/briandoconnor/fastqc/blob/master/sample.fastq.gz?raw=true"
}
],
"tar_files": [
{
"class": "File",
"path": "https://github.com/briandoconnor/fastqc/blob/master/sample.tar?raw=true"
}
],
"zipped_file" : {
"class": "File",
"path": "/tmp/fastqc_reports.tar.gz"
}
}
You can leave out either the fastq_files or tar_files as well.
Run it using the dockstore CLI:
dockstore tool launch --entry fastqc.cwl --local-entry --json fastqc.json