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Bioinformatics Analysis of Whole Exome Sequencing Data

  • Peter J. Ulintz
  • Weisheng Wu
  • Chris M. Gates
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 1881)

Abstract

This chapter contains a step-by-step protocol for identifying somatic SNPs and small Indels from next-generation sequencing data of tumor samples and matching normal samples. The workflow presented here is largely based on the Broad Institute’s “Best Practices” guidelines and makes use of their Genome Analysis Toolkit (GATK) platform. Variants are annotated with population allele frequencies and curated resources such as GnomAD and ClinVar and curated effect predictions from dbNSFP using VCFtools, SnpEff, and SnpSift.

Key words

Next-generation sequencing Cancer research Exome sequencing Genome sequencing Clinical genomics Somatic variant detection Variant annotation 

Notes

Acknowledgments

The authors would like to thank the institutions, developers, and documenters of the informatics tools used in this chapter’s workflows. Genomics and disease research in general benefits hourly from the availability of tools such as Bioconda, BWA, GATK, HaplotypeCaller, Mutect2, Samtools, SNPEff , VarScan, and Vcftools, as well as public resources such as ClinVar and GnomAD.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Peter J. Ulintz
    • 1
    • 2
  • Weisheng Wu
    • 1
  • Chris M. Gates
    • 1
  1. 1.BRCF Bioinformatics CoreUniversity of MichiganAnn ArborUSA
  2. 2.Division of Hematology and Oncology, Department of Internal MedicineUniversity of MichiganAnn ArborUSA

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