A comparative study on gene-set analysis methods for assessing differential expression associated with the survival phenotype.

ABSTRACT:

Background

Many gene-set analysis methods have been previously proposed and compared through simulation studies and analysis of real datasets for binary phenotypes. We focused on the survival phenotype and compared the performances of Gene Set Enrichment Analysis (GSEA), Global Test (GT), Wald-type Test (WT) and Global Boost Test (GBST) methods in a simulation study and on two ovarian cancer data sets. We considered two versions of GSEA by allowing different weights: GSEA1 uses equal weights, yielding results similar to the Kolmogorov-Smirnov test; while GSEA2's weights are based on the correlation between genes and the phenotype.

Results

We compared GSEA1, GSEA2, GT, WT and GBST in a simulation study with various settings for the correlation structure of the genes and the a

SUBMITTER: Lee S 

PROVIDER: S-EPMC3196970 | biostudies-literature | 2011 Sep

REPOSITORIES: biostudies-literature