Prepared by the eResearch Office, QUT.
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Prepare a sample sheet file that specifies the input files to be used. To do this, we use an nf-core script to generate the ‘samplesheet.csv’ file as follows (setting strandedness to auto allows the pipeline to determine the strandedness of your RNA-seq data automatically):
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#load python 3.710 module load python/3.910.68-gcccore-1112.2.0 #download script and make executable wget -L https://raw.githubusercontent.com/nf-core/rnaseq/master/bin/fastq_dir_to_samplesheet.py chmod +x fastq_dir_to_samplesheet.py #generate the samplesheet.csv file ./fastq_dir_to_samplesheet.py /path/to/directory/containing/fastq_files/ samplesheet.csv \ --strandedness unstrandedauto \ --read1_extension _R1.fastq.gz \ --read2_extension _R2.fastq.gz |
Example index.csv (Version 3.10.1):
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sample,fastq_1,fastq_2,strandedness control_1,/path/to/directory/containing/fastq_files/control-1_R1.fastq.gz,/path/to/directory/containing/fastq_files/control-1_R2.fastq.gz,unstrandedauto control_2,/path/to/directory/containing/fastq_files/control-2_R1.fastq.gz,/path/to/directory/containing/fastq_files/control-2_R2.fastq.gz,unstrandedauto control_3,/path/to/directory/containing/fastq_files/control-3_R1.fastq.gz,/path/to/directory/containing/fastq_files/control-3_R2.fastq.gz,unstrandedauto infected_1,/path/to/directory/containing/fastq_files/infected-1_R1.fastq.gz,/path/to/directory/containing/fastq_files/infected-1_R2.fastq.gz,unstrandedauto infected_2,/path/to/directory/containing/fastq_files/infected-1_R1.fastq.gz,/path/to/directory/containing/fastq_files/infected-2_R2.fastq.gz,unstrandedauto infected_3,/path/to/directory/containing/fastq_files/infected-1_R1.fastq.gz,/path/to/directory/containing/fastq_files/infected-3_R2.fastq.gz,unstrandedauto |
Preparing to run on the HPC
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#delete the existing assests associated with the RNAseq pipeline: cd ~/.nextflow/assets/nf-core rm -r rnaseq/ #run again a test with the new version that you are testing, for example, version 3.10.1. See details on how to run a test above (under 'Getting Started') |
Add output folders/files
sample data
Running the pipeline using custom data
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