Rhodes Daniel R, Chinnaiyan Arul M
Department of Pathology, Comprehensive Cancer Center, University of Michigan Medical School, Ann Arbor, Michigan 48109, USA.
Nat Genet. 2005 Jun;37 Suppl:S31-7. doi: 10.1038/ng1570.
DNA microarrays have been widely applied to the study of human cancer, delineating myriad molecular subtypes of cancer, many of which are associated with distinct biological underpinnings, disease progression and treatment response. These primary analyses have begun to decipher the molecular heterogeneity of cancer, but integrative analyses that evaluate cancer transcriptome data in the context of other data sources are often capable of extracting deeper biological insight from the data. Here we discuss several such integrative computational and analytical approaches, including meta-analysis, functional enrichment analysis, interactome analysis, transcriptional network analysis and integrative model system analysis.
DNA微阵列已广泛应用于人类癌症研究，描绘了无数癌症分子亚型，其中许多与不同的生物学基础、疾病进展和治疗反应相关。这些初步分析已开始解读癌症的分子异质性，但在其他数据源背景下评估癌症转录组数据的整合分析通常能够从数据中提取更深入的生物学见解。在此，我们讨论几种这样的整合计算和分析方法，包括荟萃分析、功能富集分析、相互作用组分析、转录网络分析和整合模型系统分析。
