A basic pipeline for quantification of genomic features from short read data implemented with Nextflow.

• Unix-like operating system (Linux, macOS, etc)
• Java 8

1. If you don't have it already install Docker in your computer. Read more here.

2. Install Nextflow (version 20.07.x or higher):

    curl -s https://get.nextflow.io | bash
   

3. Launch the pipeline execution:

    ./nextflow run nextflow-io/rnaseq-nf -with-docker
   

4. When the execution completes open in your browser the report generated at the following path:

    results/multiqc_report.html 
   

You can see an example report at the following link.

Note: the very first time you execute it, it will take a few minutes to download the pipeline from this GitHub repository and the associated Docker images needed to execute the pipeline.

RNASeq-NF execution relies on Nextflow framework which provides an abstraction between the pipeline functional logic and the underlying processing system.

This allows the execution of the pipeline in a single computer or in a HPC cluster without modifying it.

Currently the following resource manager platforms are supported:

• Univa Grid Engine (UGE)
• Platform LSF
• SLURM
• PBS/Torque

By default the pipeline is parallelized by spawning multiple threads in the machine where the script is launched.

To submit the execution to a UGE cluster create a file named nextflow.config in the directory where the pipeline is going to be executed with the following content:

process {
  executor='uge'
  queue='<queue name>'
}

To lean more about the avaible settings and the configuration file read the Nextflow documentation.

RNASeq-NF uses the following software components and tools:

• Salmon 1.0.0
• FastQC 0.11.5
• Multiqc 1.5