Integrative analysis of prognosis data on multiple cancer subtypes.
Ontology highlight
ABSTRACT: In cancer research, profiling studies have been extensively conducted, searching for genes/SNPs associated with prognosis. Cancer is diverse. Examining the similarity and difference in the genetic basis of multiple subtypes of the same cancer can lead to a better understanding of their connections and distinctions. Classic meta-analysis methods analyze each subtype separately and then compare analysis results across subtypes. Integrative analysis methods, in contrast, analyze the raw data on multiple subtypes simultaneously and can outperform meta-analysis methods. In this study, prognosis data on multiple subtypes of the same cancer are analyzed. An AFT (accelerated failure time) model is adopted to describe survival. The genetic basis of multiple subtypes is described using the heterogen
SUBMITTER: Liu J
PROVIDER: S-EPMC4209207 | biostudies-literature | 2014 Sep
REPOSITORIES: biostudies-literature
ACCESS DATA