title: Computational analysis in cancer exome sequencing.
abstract: 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.
authors.affiliation: Department of Pathology, Yale University School of Medicine, New Haven, CT, USA.
authors.forename: Perry
authors.initials: P
authors.lastname: Evans
authors.forename: Yong
authors.initials: Y
authors.lastname: Kong
authors.forename: Michael
authors.initials: M
authors.lastname: Krauthammer
mesh_terms: D019295:Computational Biology / Q000379:methods; D056915:DNA Copy Number Variations; D059472:Exome; D059014:High-Throughput Nucleotide Sequencing; D006801:Humans; D054643:INDEL Mutation; D019656:Loss of Heterozygosity; D009154:Mutation; D009369:Neoplasms / Q000235:genetics*; D020641:Polymorphism, Single Nucleotide