Usage and parameters

Usage (default)

By default, the pipeline looks for FastQ ending in .fastq.gz files in the current directory. Paired or single-end data are handled transparently if your paired data are tag with the R1/R2 strings (see later).

cd data_directory_with_fastq_files
sequana_fastqc

This step prepares the pipeline. If everything went well, you should see something like that:

INFO   [sequana.pipelines_common]:  Welcome to Sequana pipelines suite (sequana.readthedocs.io)
INFO   [sequana.pipelines_common]:  Found 12 files matching your input pattern (*fastq.gz)
INFO   [sequana.pipelines_common]:  readtag: _R[12]_
INFO   [sequana.pipelines_common]:  Found 6 projects/samples
INFO   [sequana.pipelines_common]: Your input data seems to be made of paired reads
Once ready execute the script fastqc.sh using
    cd fastqc; sh fastqc.sh

Check that the information are correct and follow the instructions to execute the pipeline:

cd fastqc
sh fastqc.sh

If you do a local run, the last command will execute a snakemake pipeline locally. If you are on a SLURM cluster, the script fastqc.sh should already incorporate the slurm options and you just need to type:

cd fastqc
srun -c 1 sh fastqc.sh  
# or sbatch -c 1 --wrap "sh fastqc.sh"

In both cases, once done, go to the output directory and open the summary.html file. If everything is fine, you can clean up the directory as follows:

make clean

In the summary.html file, you entry point looks like in the following image. From there you get a quick overview of the quality of the run. You can find links to individual fastqc report as well as a multiqc report:

Change the input and output directory.

sequana_fastqc --input ~/data/project1 --output ~/my_fastqc/project1_qc
cd project1_qc
sh fastqc.sh

Tune the SLURM options

By default, if the sbatch command is found, the pipeline will consider that you are on a SLURM cluster and will set default options for you (e.g. memory of 4Gb). This will be super-seed by the pipeline requirements, which can be found in the file cluster_config.json

Use more jobs

By default, locally we will use 4 jobs. On a cluster, we define the number of jobs to 40. If you wish to use more, just use the --jobs options when initialising the pipeline:

sequana_fastqc --jobs 100

Note that by default fastqc tool will use 4 cores per job. So here, you will be able to analyse 100 samples launching 100 fastqc, each of them asking for 4 cores.