title: Patient-oriented gene set analysis for cancer mutation data.
abstract: Recent research has revealed complex heterogeneous genomic landscapes in human cancers. However, mutations tend to occur within a core group of pathways and biological processes that can be grouped into gene sets. To better understand the significance of these pathways, we have developed an approach that initially scores each gene set at the patient rather than the gene level. In mutation analysis, these patient-oriented methods are more transparent, interpretable, and statistically powerful than traditional gene-oriented methods.
authors.affiliation: Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, 615 N, Wolfe Street, Baltimore, MD 21205, USA.
authors.forename: Simina M
authors.initials: SM
authors.lastname: Boca
authors.forename: Kenneth W
authors.initials: KW
authors.lastname: Kinzler
authors.forename: Victor E
authors.initials: VE
authors.lastname: Velculescu
authors.forename: Bert
authors.initials: B
authors.lastname: Vogelstein
authors.forename: Giovanni
authors.initials: G
authors.lastname: Parmigiani
mesh_terms: D019295:Computational Biology / Q000379:methods; D004252:DNA Mutational Analysis; D020869:Gene Expression Profiling / Q000379:methods*; D052138:Genes, Neoplasm; D015894:Genome, Human; D006801:Humans; D046228:Microarray Analysis; D008957:Models, Genetic; D009154:Mutation; D009369:Neoplasms / Q000235:genetics*; D012680:Sensitivity and Specificity