I'd like to share GATES, a recently published tool from our group that automates end-to-end whole-exome sequencing analysis for somatic and germline variant analysis. The publication can be found here.
The WES analysis process involves multi-step workflows, numerous interdependent software tools, and careful parameterization to ensure accuracy and reproducibility. This presents a challenge for many researchers, especially those with limited computational backgrounds. Here, we created an automated pipeline that implements the GATK Best Practices for sample preprocessing and somatic/germline variant discovery. GATES also automatically annotates variants and selects those likely to be pathogenic.
The pipeline requires only raw FASTQ files, a reference genome file, and exome-capture regions. The figure summarizes the three modules of the pipeline, each of which are run as a single command through the command line or GUI.
More information about the pipeline and our motivation can be found on GitHub or the publication. Feel free to use and report any bugs, comments, questions.
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Nicholas •
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Fig 1 - GATES runs only MuTect2 and HaplotypeCaller for small substitutions and indels. Sarek runs many more callers including for CNVs, SVs, MSI - and is easily configurable to run the subset that GATES does. If the goal was to save users from having to read Nextflow/Sarek documentation, then GATES could have been a simple bash wrapper around something like:
nextflow run nf-core/sarek -profile test --wes --tools mutect2,haplotypecaller
Fig 2A - If the goal is to "lower technical barriers to WES" then implement post-GATK filters to produce germline/somatic variant lists at ~100% precision, so that users can get to work immediately on variant interpretation without worrying about technical artifacts.
Fig 2C - Runtime does not improve beyond 4 cores because GATK's variant callers are crap at parallelism. This is why GATK re-implementations like Sentieon and Parabricks exist - that Sarek has support for.
Ultimately, GATES is a reminder of the trade-off between customizing a community-maintained pipeline for your needs vs. building your own pipeline with scripts.
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https://nf-co.re/sarek/3.10.0 ?
Per publication, GATES decreases runtimes compared to nf-core/sarek. Additionally, nf-core still requires significant parameterization and tool selection. GATES automatically implements the GATK Best Practices. Although nf-core/sarek is more customizable and may be appropriate for more complex analyses, GATES allows wet-lab scientists, clinicians, and those with limited computational experience to quickly implement basic WES analysis.