lifebit-ai / nextflow_variant_calling Goto Github PK

Mapping NGS reads to a reference and variant calling

To execute the pipeline on your computer, first pull the docker image

docker pull hadrieng/variant_calling

Then execute the workflow

nextflow run variant_calling.nf

It will produce a vcf file for the sample data present in this directory.

• Specifies the location of the reads fastq file
• By default it is set to data/SRR957824.fastq

• Specifies the mode for running the pipeline
• It must be ion or illumina
• If set ion, non adapter trimming will be performed
• If set to illumina, see option --adapt below

• Optional. It is used by --mode illumina
• Specifies the location of the adapters file for adapter trimming
• It must end in .fasta
• By default it is set to data/adapters.fasta

The SGBC cluster uses a module system. Pulling the docker image is not required!

By default, the pipeline runs locally using docker. If you run the nonpareil pipeline on the SGBC cluster, please pass the option -profile planet

Example:

nextflow run nonpareil.nf -profile planet --reads /proj/my_proj/data/reads.fastq --mode illumina --adapt custom_adapters.fasta

If you use this pipeline in your research, please cite:

• Buffalo Vince (2011), Scythe: A Bayesian adapter trimmer [Software]. Available at https://github.com/vsbuffalo/scythe
• Joshi NA, Fass JN. (2011). Sickle: A sliding-window, adaptive, quality-based trimming tool for FastQ files [Software].Available at https://github.com/najoshi/sickle.
• Ben Langmead et al.. 2009. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biology 10:R25. doi: 10.1186/gb-2009-10-3-r25
• Li H et al. 2009. The Sequence alignment/map (SAM) format and SAMtools. Bioinformatics, 25, 2078-9. doi: 10.1093/bioinformatics/btp352