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Aims
Test and run the nextflow nf-core/sarek pipeline in the HPC cluster using public data. Exercises include:
Running a test to verify the execution of the pipeline
Running the sarek variant calling pipeline with a HapMap trio data
Running the sarek variant calling pipeline with liver samples
Work in the HPC |
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Before we start using the HPC, let’s start an interactive session:
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mkdir -p $HOME/workshop/sarek/scripts cp /work/training/sarek/scripts/* $HOME/workshop/sarek/scripts/ ls -l $HOME/workshop/sarek/scripts/ |
Line 1: The -p indicates create 'parental directories as required. Thus the line 1 command creates both /workshop/ and the subfolder /workshop/scripts/
Line 2: Copies all files from /work/datasets/workshop/scripts/ as noted by an asterisk to the newly created folder $HOME/workshop/scripts/
Copy public data to your $HOME
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mkdir -p $HOME/workshop/sarek/data/WES/trio mkdir -p $HOME/workshop/sarek/data/WES/liver cp /work/training/sarek/data/WES/trio/* $HOME/workshop/sarek/data/WES/trio cp /work/training/sarek/data/WES/liver/* $HOME/workshop/sarek/data/WES/liver |
Lines 1 -2: Command creates the folders to copy data
Lines 2 - Line 3: Copies all files from /work/datasets/workshop/sarek/data/WES/trio folder as noted by an asterisk to newly created $HOME/workshop/sarek/data/WES/trio folder.
Line 4: Copies all files from /work/datasets/workshop/sarek/scriptsdata/WES/liver folder as noted by an asterisk to newly created $HOME/workshop/sarek/scriptsdata/WES/liver folder.
Create a folder folders for running the nf-RNA-seq core/sarek pipeline
Let’s create an “RNAseq” folder to run the nf-core/rnaseq pipeline and move into it. For example:
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mkdir -p $HOME/workshop/sarek mkdir $HOME/workshop/sarek/run1_test mkdir $HOME/workshop/sarek/run2_trio mkdir $HOME/workshop/sarek/run3_liver cd $HOME/workshop/ |
Lines 1-4: create sub-folders for each exercise
Line 5: change the directory to the folder “run1_test”
Line 6: print the current working directory
Exercise 1: Running a test with nf-core sample data
First, let’s assess the execution of the nf-core/rnaseq pipeline by running a test using sample data.
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#!/bin/bash -l #PBS -N nfsarek_run1_test #PBS -l walltime=48:00:00 #PBS -l select=1:ncpus=1:mem=5gb cd $PBS_O_WORKDIR NXF_OPTS='-Xms1g -Xmx4g' module load java #specify the nextflow version to use to run the workflow export NXF_VER=23.10.1 #run the sarek pipeline nextflow run nf-core/sarek \ -r 3.3.2 \ -profile test,singularity \ --outdir ./results |
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nextflow command: nextflow run
pipeline name: nf-core/sarek
pipeline version: -r 3.3.2
container type and sample data: -profile test,singularity
output directory: --outdir results
Submitting the job
Submit the test job to the HPC cluster as follows:
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results/
├── csv
│ ├── markduplicates.csv
│ ├── markduplicates_no_table.csv
│ ├── recalibrated.csv
│ └── variantcalled.csv
├── multiqc
│ ├── multiqc_data
│ ├── multiqc_plots
│ └── multiqc_report.html
├── pipeline_info
│ ├── execution_report_2024-05-08_15-28-38.html
│ ├── execution_timeline_2024-05-08_15-28-38.html
│ ├── execution_trace_2024-05-08_15-28-38.txt
│ ├── params_2024-05-08_15-41-30.json
│ ├── pipeline_dag_2024-05-08_15-28-38.html
│ └── software_versions.yml
├── preprocessing
│ ├── markduplicates
│ ├── recalibrated
│ └── recal_table
├── reports
│ ├── bcftools
│ ├── fastqc
│ ├── markduplicates
│ ├── mosdepth
│ ├── samtools
│ └── vcftools
├── tabix
│ ├── genome.bed.gz
│ └── genome.bed.gz.tbi
└── variant_calling
└── strelka |
Exercise 2: Run nf-core/sarek using trio data
The pipeline requires preparing at least 2 files:
Metadata file (samplesheet.csv) thatspecifies the following information:
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patient,sample,lane,fastq_1,fastq_2 ID1,S1,L002,/full/path/to/ID1_S1_L002_R1_001.fastq.gz,/full/path/to/ID1_S1_L002_R2_001.fastq.gz |
PBS Pro script (launch_nf-core_sarek_trio.pbs) with instructions to run the pipeline
Create the metadata file (samplesheet.csv):
Change to the data folder directory:
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cd $HOME/workshop/sarek/data/trio pwd |
Copy the bash script python script “create_samplesheet_nf-core_sarek.py" to the working folder
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cp /work/training/sarek/scripts/create_samplesheet_nf-core_sarek.shpy $HOME/workshop/sarek/data/trio |
Note: you could replace ‘$HOME/workshop/sarek/data’ with “.” A dot indicates ‘current directory’ and will copy the file to the directory where you are currently located
Check help option on how to run the script:
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usage: create_samplesheet_nf-core_sarek.py [-h] [--dir DIR] [--read1_extension READ1_EXTENSION] [--read2_extension READ2_EXTENSION] [--out OUT] Extract metadata from fastq files in a directory. optional arguments: -h, --help show this help message and exit --dir DIR Directory to search for files (default: current directory) --read1_extension READ1_EXTENSION Extension for fastq_1 files (default: R1_001.fastq.gz) --read2_extension READ2_EXTENSION Extension for fastq_2 files (default: R2_001.fastq.gz) --out OUT Output metadata CSV file |
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Example for Whole Exome Sequencing (WES) data -:
Let’s generate the metadata file by running the following command:
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python create_samplesheet_nf-core_sarek.py --dir $HOME/workshop/sarek/data/trio \ --read1_extension R1.fastq.gz \ --read2_extension R2.fastq.gz \ --out samplesheet.csv |
Check the newly created samplesheet.csv file:
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Copy the PBS Pro script for QC (launch_nf-core_RNAseq_QC.pbs)
Copy and paste the code below to the terminal:
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cp $HOME/workshop/data/samplesheet.csv $HOME/workshop/RNAseq/run2_QC cp $HOME/workshop/scripts/launch_nf-core_RNAseq_QC.pbs $HOME/workshop/RNAseq/run2_QC cd $HOME/workshop/RNAseq/run2_QC |
Line 1: Copy the samplesheet.csv file to the working directory
Line 2: move to the working directory
Line 3: copy the launch_nf-core_RNAseq_QC.pbs submission script to the working directory
View the content of the launch_nf-core_RNAseq_QC.pbs script:
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#!/bin/bash -l #PBS -N nfrnaseq_QC #PBS -l select=1:ncpus=2:mem=4gb #PBS -l walltime=24:00:00 #work on current directory cd $PBS_O_WORKDIR #load java and set up memory settings to run nextflow module load java export NXF_OPTS='-Xms1g -Xmx4g' nextflow run nf-core/rnaseq \ -profile singularity \ -r 3.12.0 \ --input samplesheet.csv \ --outdir results \ --genome GRCm38-local \ --skip_trimming \ --skip_alignment \ --skip_pseudo_alignment |
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We recommend running the nextflow nf-core/rnaseq pipeline once and then assessing the fastqc results folder to assess if sequence biases are present in the 5'-end and 3'-end ends of the sequences.
Version 3.12.0 allows running the pipeline to do quality assessment only, without any alignment, read counting, or trimming.
Submitting the job
Once you have created the folder for the run, the samplesheet.csv file, and launch.pbs, you are ready to submit the job to the HPC scheduler:
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Once the pipeline has finished running - Assess the QC report:
NOTE: To proceed, you need to be on QUT’s WiFi network or signed via VPN.
To browse the working folder in the HPC type in the file finder:
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Assess QC reports (FastQC and MultiQC) to define how many nucleotides should be trimmed from the 5'-end and/or 3-end regions of the FASTQ reads (see Case 3 below).
Exercise 3: Healthy vs. disease liver samples
Copy and paste the code below to the terminal:
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cp $HOME/workshop/data/samplesheet.csv $HOME/workshop/RNAseq/run3_RNAseq cd $HOME/workshop/RNAseq/run3_RNAseq pwd |
Line 1: Copy the samplesheet.csv file to the working directory
Line 2: move to the working directory
Line 3: print working directory → verify the folder location
Copy the PBS Pro script to run the nf-core/rnaseq pipeline:
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