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MAVTgsa: An R Package for Gene Set (Enrichment) Analysis
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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4101957/ https://www.ncbi.nlm.nih.gov/pubmed/25101274 http://dx.doi.org/10.1155/2014/346074 |
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author | Chien, Chih-Yi Chang, Ching-Wei Tsai, Chen-An Chen, James J. |
author_facet | Chien, Chih-Yi Chang, Ching-Wei Tsai, Chen-An Chen, James J. |
author_sort | Chien, Chih-Yi |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-4101957 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-41019572014-08-06 MAVTgsa: An R Package for Gene Set (Enrichment) Analysis Chien, Chih-Yi Chang, Ching-Wei Tsai, Chen-An Chen, James J. Biomed Res Int Research Article 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. Hindawi Publishing Corporation 2014 2014-07-03 /pmc/articles/PMC4101957/ /pubmed/25101274 http://dx.doi.org/10.1155/2014/346074 Text en Copyright © 2014 Chih-Yi Chien et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Chien, Chih-Yi Chang, Ching-Wei Tsai, Chen-An Chen, James J. MAVTgsa: An R Package for Gene Set (Enrichment) Analysis |
title | MAVTgsa: An R Package for Gene Set (Enrichment) Analysis |
title_full | MAVTgsa: An R Package for Gene Set (Enrichment) Analysis |
title_fullStr | MAVTgsa: An R Package for Gene Set (Enrichment) Analysis |
title_full_unstemmed | MAVTgsa: An R Package for Gene Set (Enrichment) Analysis |
title_short | MAVTgsa: An R Package for Gene Set (Enrichment) Analysis |
title_sort | mavtgsa: an r package for gene set (enrichment) analysis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4101957/ https://www.ncbi.nlm.nih.gov/pubmed/25101274 http://dx.doi.org/10.1155/2014/346074 |
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