Computational Analysis in Cancer Exome Sequencing

  • Perry Evans
  • Yong Kong
  • Michael KrauthammerEmail author
Part of the Methods in Molecular Biology book series (MIMB, volume 1176)


Exome sequencing in cancer is a powerful tool for identifying mutational events across the coding region of human genes. Here, we describe computational methods that use exome sequencing reads from cancer samples to identify somatic single nucleotide variants (SNVs), copy number alterations, and short insertions and deletions (InDels). We further describe analytical methods to generate lists of driver genes with more mutational events than expected by chance.

Key words

Cancer Single nucleotide variant Copy number variation Exome sequencing Gene burden InDels 



This work was supported by the Yale SPORE in Skin Cancer funded by the National Cancer Institute grant number 1 P50 CA121974 (principal investigator, Ruth Halaban), the Melanoma Research Alliance (a Team award to Ruth Halaban and M.K.), The National Library of Medicine Training grant 5T15LM007056 (P.E.), Yale Comprehensive Cancer Center (M.K.), and Gilead Sciences, Inc. (M.K.).


  1. 1.
    Kong Y (2011) Btrim: a fast, lightweight adapter and quality trimming program for next-generation sequencing technologies. Genomics 98(2):152–153PubMedCrossRefGoogle Scholar
  2. 2.
    Li H, Durbin R (2009) Fast and accurate short read alignment with Burrows–Wheeler transform. Bioinformatics 25(14):1754–1760PubMedCentralPubMedCrossRefGoogle Scholar
  3. 3.
    Li H et al (2009) The sequence alignment/map format and SAMtools. Bioinformatics 25(16):2078–2079PubMedCentralPubMedCrossRefGoogle Scholar
  4. 4.
    Li J et al (2012) CONTRA: copy number analysis for targeted resequencing. Bioinformatics 28(10):1307–1313PubMedCentralPubMedCrossRefGoogle Scholar
  5. 5.
    Zhang Q et al (2010) CMDS: a population-based method for identifying recurrent DNA copy number aberrations in cancer from high-resolution data. Bioinformatics 26(4):464–469PubMedCentralPubMedCrossRefGoogle Scholar
  6. 6.
    Krzywinski M et al (2009) Circos: an information aesthetic for comparative genomics. Genome Res 19(9):1639–1645PubMedCentralPubMedCrossRefGoogle Scholar
  7. 7.
    Thorvaldsdottir H, Robinson JT, Mesirov JP (2012) Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration. Brief Bioinform 14(2):178–192PubMedCentralPubMedCrossRefGoogle Scholar
  8. 8.
    Krauthammer M et al (2012) Exome sequencing identifies recurrent somatic RAC1 mutations in melanoma. Nat Genet 44(9):1006–1014PubMedCentralPubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  1. 1.Department of PathologyYale University School of MedicineNew HavenUSA
  2. 2.W.M. Keck Foundation Biotechnology Resource Laboratory, Department of Molecular Biophysics and BiochemistryYale University School of MedicineNew HavenUSA

Personalised recommendations