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Prepared by the eResearch Office, QUT.

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  nextflow run nf-core/rnaseq \
      --input samplesheetindex.csv \
      --genome GRCm38 \
      --aligner star_salmon \
      -profile singularity \
      -r 3.3

Note, if the running was interrupted or did not complete a particular step or you want to modify a parameter for a particular step, instead of re-running all process again nextflow enables to “-resume” the workflow.

  nextflow run nf-core/rnaseq \
      --input samplesheetindex.csv \
      --genome GRCm38 \
      --aligner star \
      -profile singularity \
      -r 3.3 \
      -resume

Preparing a ‘samplesheet.csv’ file

A samplesheetPrepare an index.csv file tells containing the workflow the location of the read 1 (R1), read 2 (R2) and other information about the samples including ‘group’ (i.e., control or infected), replicate number and the orientation of the reads (i.e., forward, reverse, unstranded). Example samplesheetinformation of the samples to be processed. See below examples of index.csv files.

Example index.csv (previous versions):

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To run this on the HPC a PBS submission script needs to be created .In the folder you have created for this run create using a text editor. For example, create a file called launch.pbs using a text editor of choice (i.e., vim, vi or nano) and then copy and paste the code below:

#!/bin/bash -l
#PBS -N nfrna2
#PBS -l select=1:ncpus=2:mem=4gb
#PBS -l walltime=24:00:00

cd $PBS_O_WORKDIR
module load java
NXF_OPTS='-Xms1g -Xmx4g'

nextflow run nf-core/rnaseq -profile singularity -r 3.3 --input index.csv --genome GRCm38 --aligner star_salmon

Additional options:We recommend running the nextflow nf-core/rnaseq pipeline once and then assess the fastqc results folder to assess if sequence biases are present in the 5'-end and 3'-end ends of the sequences. Then, we can use the PBS script below to tell the pipeline to remove a defined number of bases from the 5'-end (--clip_r1 or --clip_r2) or 3'-end (--three_prime_clip_r1 or --three_prime_clip_r2). Also we can specify to remove ribosomal RNA as these sets of sequences are non-informative.

#!/bin/bash -l
#PBS -N nfrna2
#PBS -l select=1:ncpus=2:mem=4gb
#PBS -l walltime=24:00:00

#work on current directory (folder)
cd $PBS_O_WORKDIR

#load java and set up memory settings to run nextflow
module load java
NXF_OPTS='-Xms1g -Xmx4g'

#run the rnaseq pipeline
#with-dag can output files in .png, .pdf, .svg or .html
nextflow run nf-core/rnaseq -profile conda  --input samplesheet.csv \
        --genome GRCm38 \
        --aligned star_rsem \
        --min_mapped_reads 5 \
        --clip_r1 10 \
        --clip_r2 10 \
        --three_prime_clip_r1 2 \
        --three_prime_clip_r2 2 \
        --remove_ribo_rna \
        -dump-channels \
        -with-dag flowchart.png

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