从FastQ数据到高可信度变异检测：基因组分析工具包最佳实践流程
From FastQ data to high confidence variant calls: the Genome Analysis Toolkit best practices pipeline.
作者信息
Van der Auwera Geraldine A, Carneiro Mauricio O, Hartl Christopher, Poplin Ryan, Del Angel Guillermo, Levy-Moonshine Ami, Jordan Tadeusz, Shakir Khalid, Roazen David, Thibault Joel, Banks Eric, Garimella Kiran V, Altshuler David, Gabriel Stacey, DePristo Mark A
机构信息
Genome Sequencing and Analysis Group, Broad Institute, Cambridge, Massachusetts.
Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom.
出版信息
Curr Protoc Bioinformatics. 2013;43(1110):11.10.1-11.10.33. doi: 10.1002/0471250953.bi1110s43.
Abstract
This unit describes how to use BWA and the Genome Analysis Toolkit (GATK) to map genome sequencing data to a reference and produce high-quality variant calls that can be used in downstream analyses. The complete workflow includes the core NGS data processing steps that are necessary to make the raw data suitable for analysis by the GATK, as well as the key methods involved in variant discovery using the GATK.
摘要
本单元介绍如何使用BWA和基因组分析工具包（GATK）将基因组测序数据比对到参考序列，并生成可用于下游分析的高质量变异位点调用结果。完整的工作流程包括使原始数据适合GATK分析所需的核心NGS数据处理步骤，以及使用GATK进行变异位点发现所涉及的关键方法。
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