Cargando…
NGSEA: Network-Based Gene Set Enrichment Analysis for Interpreting Gene Expression Phenotypes with Functional Gene Sets
Gene set enrichment analysis (GSEA) is a popular tool to identify underlying biological processes in clinical samples using their gene expression phenotypes. GSEA measures the enrichment of annotated gene sets that represent biological processes for differentially expressed genes (DEGs) in clinical...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Korean Society for Molecular and Cellular Biology
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6715341/ https://www.ncbi.nlm.nih.gov/pubmed/31307154 http://dx.doi.org/10.14348/molcells.2019.0065 |
_version_ | 1783447216951656448 |
---|---|
author | Han, Heonjong Lee, Sangyoung Lee, Insuk |
author_facet | Han, Heonjong Lee, Sangyoung Lee, Insuk |
author_sort | Han, Heonjong |
collection | PubMed |
description | Gene set enrichment analysis (GSEA) is a popular tool to identify underlying biological processes in clinical samples using their gene expression phenotypes. GSEA measures the enrichment of annotated gene sets that represent biological processes for differentially expressed genes (DEGs) in clinical samples. GSEA may be suboptimal for functional gene sets; however, because DEGs from the expression dataset may not be functional genes per se but dysregulated genes perturbed by bona fide functional genes. To overcome this shortcoming, we developed network-based GSEA (NGSEA), which measures the enrichment score of functional gene sets using the expression difference of not only individual genes but also their neighbors in the functional network. We found that NGSEA outperformed GSEA in identifying pathway gene sets for matched gene expression phenotypes. We also observed that NGSEA substantially improved the ability to retrieve known anti-cancer drugs from patient-derived gene expression data using drug-target gene sets compared with another method, Connectivity Map. We also repurposed FDA-approved drugs using NGSEA and experimentally validated budesonide as a chemical with anti-cancer effects for colorectal cancer. We, therefore, expect that NGSEA will facilitate both pathway interpretation of gene expression phenotypes and anti-cancer drug repositioning. NGSEA is freely available at www.inetbio.org/ngsea. |
format | Online Article Text |
id | pubmed-6715341 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Korean Society for Molecular and Cellular Biology |
record_format | MEDLINE/PubMed |
spelling | pubmed-67153412019-09-06 NGSEA: Network-Based Gene Set Enrichment Analysis for Interpreting Gene Expression Phenotypes with Functional Gene Sets Han, Heonjong Lee, Sangyoung Lee, Insuk Mol Cells Articles Gene set enrichment analysis (GSEA) is a popular tool to identify underlying biological processes in clinical samples using their gene expression phenotypes. GSEA measures the enrichment of annotated gene sets that represent biological processes for differentially expressed genes (DEGs) in clinical samples. GSEA may be suboptimal for functional gene sets; however, because DEGs from the expression dataset may not be functional genes per se but dysregulated genes perturbed by bona fide functional genes. To overcome this shortcoming, we developed network-based GSEA (NGSEA), which measures the enrichment score of functional gene sets using the expression difference of not only individual genes but also their neighbors in the functional network. We found that NGSEA outperformed GSEA in identifying pathway gene sets for matched gene expression phenotypes. We also observed that NGSEA substantially improved the ability to retrieve known anti-cancer drugs from patient-derived gene expression data using drug-target gene sets compared with another method, Connectivity Map. We also repurposed FDA-approved drugs using NGSEA and experimentally validated budesonide as a chemical with anti-cancer effects for colorectal cancer. We, therefore, expect that NGSEA will facilitate both pathway interpretation of gene expression phenotypes and anti-cancer drug repositioning. NGSEA is freely available at www.inetbio.org/ngsea. Korean Society for Molecular and Cellular Biology 2019-08 2019-07-16 /pmc/articles/PMC6715341/ /pubmed/31307154 http://dx.doi.org/10.14348/molcells.2019.0065 Text en © The Korean Society for Molecular and Cellular Biology. All rights reserved. This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/3.0/. |
spellingShingle | Articles Han, Heonjong Lee, Sangyoung Lee, Insuk NGSEA: Network-Based Gene Set Enrichment Analysis for Interpreting Gene Expression Phenotypes with Functional Gene Sets |
title | NGSEA: Network-Based Gene Set Enrichment Analysis for Interpreting Gene Expression Phenotypes with Functional Gene Sets |
title_full | NGSEA: Network-Based Gene Set Enrichment Analysis for Interpreting Gene Expression Phenotypes with Functional Gene Sets |
title_fullStr | NGSEA: Network-Based Gene Set Enrichment Analysis for Interpreting Gene Expression Phenotypes with Functional Gene Sets |
title_full_unstemmed | NGSEA: Network-Based Gene Set Enrichment Analysis for Interpreting Gene Expression Phenotypes with Functional Gene Sets |
title_short | NGSEA: Network-Based Gene Set Enrichment Analysis for Interpreting Gene Expression Phenotypes with Functional Gene Sets |
title_sort | ngsea: network-based gene set enrichment analysis for interpreting gene expression phenotypes with functional gene sets |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6715341/ https://www.ncbi.nlm.nih.gov/pubmed/31307154 http://dx.doi.org/10.14348/molcells.2019.0065 |
work_keys_str_mv | AT hanheonjong ngseanetworkbasedgenesetenrichmentanalysisforinterpretinggeneexpressionphenotypeswithfunctionalgenesets AT leesangyoung ngseanetworkbasedgenesetenrichmentanalysisforinterpretinggeneexpressionphenotypeswithfunctionalgenesets AT leeinsuk ngseanetworkbasedgenesetenrichmentanalysisforinterpretinggeneexpressionphenotypeswithfunctionalgenesets |