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Activity Number: 306
Type: Contributed
Date/Time: Tuesday, August 5, 2014 : 8:30 AM to 10:20 AM
Sponsor: Biometrics Section
Abstract #313655 View Presentation
Title: ROMER: Rank-Based Rotation Gene Set Enrichment Analysis
Author(s): Di Wu*+
Companies: Harvard
Keywords: gene set ; enrichment analysis ; rotation
Abstract:

A gene set test is a differential expression analysis in which a P-value is assigned to a set of genes as a unit. Gene set tests are valuable for increasing statistical power, organizing and interpreting results and for relating expression patterns across different experiments. Most existing methods are based on permutation. Methods that rely on permutation of sample are limited by sample size, while those that rely on permutation of probes unrealistically assume independence of genes. We present ROMER, a statistically rigorous gene set test that allows for gene-wise correlation to test the so-called competitive null hypothesis that the genes in the gene- set are no more differentially expressed than the randomly chosen genes of the same set size in the array platform. Rank of log fold change or moderated t was used to represent the differential expression level of a gene. ROMER is not limited by sample size. It is for any experimental design that can be expressed as a linear model, and can also incorporate array weights and correlated samples. ROMER can test for uni- or bi-direction regulation. This is particularly important when testing multiple pathway gene sets, in which case t


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