1.What is GATK?

GATK stands for Genome Analysis Toolkit. It is a collection of command-line tools for analyzing high-throughput sequencing data with a primary focus on variant discovery. The tools can be used individually or chained together into complete workflows. We provide end-to-end workflows, called GATK Best Practices, tailored for specific use cases.

*Starting with version 4.0, GATK contains a copy of the Picard toolkit, so all Picard tools are available from within GATK itself. *

2.Analysis phases

(1) Data pre-processing is the first phase in all cases, and involves pre-processing the raw sequence data (provided in FASTQ or uBAM format) to produce analysis-ready BAM files. This involves alignment to a reference genome as well as some data cleanup operations to correct for technical biases and make the data suitable for analysis.

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(2) Variant discovery proceeds from analysis-ready BAM files and produces variant calls. This involves identifying genomic variation in one or more individuals and applying filtering methods appropriate to the experimental design. The output is typically in VCF format although some classes of variants (such as CNVs) are difficult to represent in VCF and may therefore be represented in other structured text-based formats.

(3) Additional steps such as filtering and annotation may be required to produce a callset ready for downstream genetic analysis, depending on the application. This typically involves using resources of known variation, truthsets and other metadata to assess and improve the accuracy of the results as well as attach additional information.

3. Clinical Whole Genome Sequencing Workflow

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4. Experimental designs

Strategy	Panel	Exome(WES)	Genome(WGS)
Size of target space (Mbp)	~ 0.5	~ 50	~ 3200
Average read depth	500–1000×	100–150×	~ 30–60×
Relative cost	$	$$	$$$
SNV/indel detection	++	++	++
CNV detection	+	+	++
SV detection	–	–	+
Low VAF	++	+	+

Reference

https://gatk.broadinstitute.org/hc/en-us/sections/360007226651-Best-Practices-Workflows
https://www.nature.com/articles/s41525-022-00295-z
https://doi.org/10.1007/s00441-017-2636-6
https://genomemedicine.biomedcentral.com/counter/pdf/10.1186/s13073-020-00791-w.pdf
https://mp.weixin.qq.com/s/8bux7uTeZC5a23yVgExLIw