Journal Article

MAVTgsa : An R Package for Gene Set (Enrichment) Analysis

Chen, James J., Chang, Ching-Wei, Chien, Chih-Yi, Tsai, Chen-An

2014

Overview

Gene set analysis methods aim to determine whether an a priori defined set of genes shows statistically significant difference in expression on either categorical or continuous outcomes. Although many methods for gene set analysis have been proposed, a systematic analysis tool for identification of different types of gene set significance modules has not been developed previously. This work presents an R package, called MAVTgsa, which includes three different methods for integrated gene set enrichment analysis. (1) The one-sided OLS (ordinary least squares) test detects coordinated changes of genes in gene set in one direction, either up- or downregulation. (2) The two-sided MANOVA (multivariate analysis variance) detects changes both up- and downregulation for studying two or more experimental conditions. (3) A random forests-based procedure is to identify gene sets that can accurately predict samples from different experimental conditions or are associated with the continuous phenotypes. MAVTgsa computes the P values and FDR (false discovery rate) q-value for all gene sets in the study. Furthermore, MAVTgsa provides several visualization outputs to support and interpret the enrichment results. This package is available online.

• Publisher: Hindawi Puplishing Corporation,Hindawi Publishing Corporation,John Wiley & Sons, Inc
• Subject: Algorithms / Analysis / Classification / Competition / Databases, Genetic / DNA microarrays / Forests / Gene expression / Gene Expression Profiling - methods / Gene Expression Regulation - genetics / Genotype & phenotype / Hypotheses / Methods / Models, Statistical / Multivariate analysis / Oligonucleotide Array Sequence Analysis - methods / Principal components analysis / Software / Statistics / Technology application