Cancer Markers Selection Using Network-Based Cox Regression: A Methodological and Computational Practice.

ABSTRACT: International initiatives such as the Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) are collecting multiple datasets at different genome-scales with the aim of identifying novel cancer biomarkers and predicting survival of patients. To analyze such data, several statistical methods have been applied, among them Cox regression models. Although these models provide a good statistical framework to analyze omic data, there is still a lack of studies that illustrate advantages and drawbacks in integrating biological information and selecting groups of biomarkers. In fact, classical Cox regression algorithms focus on the selection of a single biomarker, without taking into account the strong correlation between genes. Even though network-based Cox regression al

SUBMITTER: Iuliano A 

PROVIDER: S-EPMC4911360 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature