Create working folder and copy data
...
Install tools using conda
Approach 1: Create a conda environment and install tools one at a time
Create a conda environment called ONTvariants_QC
...
| Code Block |
|---|
conda install bioconda::seqkit |
Approach 2: Create environment and install tools all at once
This is a slower option, but it is convenient when installing many tools.
Prepare the following environment.yml file:
| Code Block |
|---|
name: ONTvariants_QC channels: - conda-forge - defaults - bioconda dependencies: - nanoplot - porechop_abi - chopper |
...
| Code Block |
|---|
#!/bin/bash -l
#PBS -N run1_QC
#PBS -l select=1:ncpus=8:mem=16gb
#PBS -l walltime=48:00:00
#PBS -m abe
cd $PBS_O_WORKDIR
conda activate ONTvariants_QC
###############################################################
# Variables
###############################################################
FASTQ='/work/training/ONTvariants/data/SRR17138639_1.fastq.gz'
GENOME='/work/training/ONTvariants/data/chr20.fasta'
SAMPLEID='SRR17138639'
###############################################################
#STEP1: NanoPlot - overall QC report
NanoPlot -t 8 --fastq $FASTQ --prefix ${SAMPLEID}_QC_ --plots dot --N50 --tsv_stats
#STEP2: porechop_abi - remove adapters
porechop_abi -abi -t 8 --input ${SAMPLEID}.fastq.gz$FASTQ --discard_middle --output ${SAMPLEID}_trimmed.fastq
#STEP3: chopper - retain reads with >Q10 and length>300b
chopper -q 10 -l 300 -i ${SAMPLEID}_trimmed.fastq > ${SAMPLEID}_trimmed_q10.fastq
#STEP4: get stats of trimmed FASTQ files
seqkit stats *.fastq > Report_trimmed_FASTQ_stats.txt |
...
As outputs find the porechop_abi processed file (SRR17138639_1_porechop_abi.fastq) and the chopper output (SRR17138639_1_porechop_abi_chopper_q10_300b.fastq). To visualise the QC reports, let’s connect to the HPC via file finder (see below).
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:
...