title: MAVTgsa: an R package for gene set (enrichment) analysis.
abstract: 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.
authors.affiliation: Community Medicine Research Center, Keelung Chang Gung Memorial Hospital, No. 200, Lane 208, Jijinyi Road, Anle District, Keelung 204, Taiwan.
authors.forename: Chih-Yi
authors.initials: CY
authors.lastname: Chien
authors.affiliation: Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, FDA, 3900 NCTR Road, HFT-20, Jefferson, AR 72079, USA.
authors.forename: Ching-Wei
authors.initials: CW
authors.lastname: Chang
authors.affiliation: Department of Agronomy, National Taiwan University, No. 1, Section 4, Roosevelt Road, Taipei 106, Taiwan.
authors.forename: Chen-An
authors.identifier: 0000-0002-7490-4331
authors.initials: CA
authors.lastname: Tsai
authors.affiliation: Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, FDA, 3900 NCTR Road, HFT-20, Jefferson, AR 72079, USA ; Graduate Institute of Biostatistics and Biostatistics Center, China Medical University, Taichung, Taiwan.
authors.forename: James J
authors.initials: JJ
authors.lastname: Chen
mesh_terms: D000465:Algorithms; D030541:Databases, Genetic; D020869:Gene Expression Profiling / Q000379:methods*; D005786:Gene Expression Regulation / Q000235:genetics; D015233:Models, Statistical; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*
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