title: Computational methods and resources for the interpretation of genomic variants in cancer.
abstract: The recent improvement of the high-throughput sequencing technologies is having a strong impact on the detection of genetic variations associated with cancer. Several institutions worldwide have been sequencing the whole exomes and or genomes of cancer patients in the thousands, thereby providing an invaluable collection of new somatic mutations in different cancer types. These initiatives promoted the development of methods and tools for the analysis of cancer genomes that are aimed at studying the relationship between genotype and phenotype in cancer. In this article we review the online resources and computational tools for the analysis of cancer genome. First, we describe the available repositories of cancer genome data. Next, we provide an overview of the methods for the detection of genetic variation and computational tools for the prioritization of cancer related genes and causative somatic variations. Finally, we discuss the future perspectives in cancer genomics focusing on the impact of computational methods and quantitative approaches for defining personalized strategies to improve the diagnosis and treatment of cancer.
authors.forename: Rui
authors.initials: R
authors.lastname: Tian
authors.forename: Malay K
authors.initials: MK
authors.lastname: Basu
authors.forename: Emidio
authors.initials: E
authors.lastname: Capriotti
mesh_terms: D019295:Computational Biology; D062126:Databases, Chemical; D014644:Genetic Variation; D015894:Genome, Human; D005838:Genotype; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods; D006801:Humans; D058977:Molecular Sequence Annotation; D009369:Neoplasms / Q000175:diagnosis* / Q000235:genetics*; D010641:Phenotype; D011379:Prognosis; D017422:Sequence Analysis, DNA / Q000379:methods; D012984:Software