Recommendations for Whole Genome Sequencing Workflow

Question

[jrleary]

My lab is looking to get into Whole Genome Sequencing, and we of course need a processing and analysis pipeline for the data we generate. I've been reading up on WGS / WES, and I understand the basics but I haven't seen any "best practices" type documents / tutorials like those that exist for single cell and bulk RNAseq (my typical work). Since this is the first time I'll have analyzed WGS data I'm less familiar with the literature surrounding the topic, and would greatly appreciate if someone could point me in the right direction.

[igor]

Check the GATK Best Practices: https://gatk.broadinstitute.org/hc/en-us

[ATpoint]

Check SpeedSeq. Unlike GATK it is not as painful to use imho.

[jrleary]

Are either of GATK or SpeedSeq capable of analyzing the microbiome of a sample? I should have clarified in my original post that that's what we're primarily interested in.

[igor]

When people discuss WGS analysis, they usually mean a single genome. The goal is to find variants (point mutations, insertions/deletions, copy number, etc.).

For metagenomics/microbiomics, the goal is usually to quantify different species. Thus, the inputs, the outputs, and the algorithms will be very different.

[jrleary]

Ah ok. Thank you for the clarification.

Answer 1

[piechota.marcin]

GATK best practices is the best place to start with Link to GATK web page. Look also at their implementation of pipeline in WDL Link to GATK Github. Later you can think about modifications like DeepVariant Link do DeepVariant Github

Answer 2

[bruce.moran]

Based on your affiliation (cancer center) you might want to look at Sarek which is a pipeline for WGS data offering both somatic and germline variant calling.

[igor]

Based on GATK Best Practices.

[bruce.moran]

Sarek includes GATK 'best practices' but is a lot more than just that.