RNA-Seq workflow for single-end data. The workflow can be downloaded and run on a cluster environment using the tool qproject provided on github: https://github.com/qbicsoftware/qproject

The workflow uses a module system to load the required software. Be sure to check the jobscript.sh file to see which software modules are required. The modules are loaded automatically when using qproject run to start the workflow, otherwise they have to be loaded manually.

One should use qproject to download the files. This also creates all folders necessary for the workflow.

qproject create -t . -w github:qbicsoftware/rnaseq

Be sure to add a config file "params.json" in etc which should look like this:

{
    "gtf": "path/to/gtf",
    "indexed_genome": "path/to/genome/basename",
    "stranded": "no",
    "overlap_mode": "union",
    "feature_type": "exon",
    "gff_attribute": "gene_id",
    "normalize_counts": "deseq2"
}

where indexed_genome and gtf are paths relative to ref.

indexed_genome is the basename of a bowtie2 index. gtf is the .gtf file of the reference genome

The parameters stranded, overlap_mode, feature_type and gff_attribute are explained in the htseq documentation.

Members of QBiC can download the data for analysis using qpostman: https://github.com/qbicsoftware/postman-cli

It should be installed on the computing stations and can be loaded with:

module load qbic/qpostman/0.1.2.3

To download the data navigate to the data folder and either provide a QBiC ID

java -jar qpostman.jar -i <QBiC ID> -u <your_qbic_username>

or a file containing the project QBiC IDs:

postman-0.1.2.3 -f sample_IDs.csv -u user-name

If you're not using qpostman just put the relevant files in the data folder (formats supported: .fastq, .fastq.gz).

To run the workflow navigate to the src folder. Using snakemake -n one can display the operations the workflow will perform. Using the --dag parameter and piping it to dot one can create a .pdf version of the directed acyclic graph used by snakemake to inspect the behavious of the workflow on a local machine.

module load qbic/anaconda
cd src/
snakemake -n
snakemake --dag | dot -Tpdf > dag.pdf

To run the workflow:

qproject run -t ..

While running one can inspect the log files (e.g. in a different screen session) for the progress and errors generated by the workflow:

cd logs/
tail snake.err -f

And to check the jobs on the computing cluster one can use qstat.

Alternatively to using qproject run one could use snakemake -j to run the workflow, but then be sure to check the jobscript.sh to load the required modules manually and also note that this would also not use qsub to submit the jobs.