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

Abstract EN

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.