Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, 615 N, Wolfe Street, Baltimore, MD 21205, USA.
Genome Biol. 2010;11(11):R112. doi: 10.1186/gb-2010-11-11-r112. Epub 2010 Nov 23.
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.
最近的研究揭示了人类癌症中复杂的异质基因组景观。然而，突变往往发生在一组可以被归类为基因集的核心途径和生物过程中。为了更好地理解这些途径的意义，我们开发了一种最初在患者而不是基因水平上对每个基因集进行评分的方法。在突变分析中，这些面向患者的方法比传统的面向基因的方法更透明、可解释和具有统计学意义。
