Multi-edge gene set networks reveal novel insights into global relationships between biological themes.

Curated gene sets from databases such as KEGG Pathway and Gene Ontology are often used to systematically organize lists of genes or proteins derived from high-throughput data. However, the information content inherent to some relationships between the interrogated gene sets, such as pathway crosstal...

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Autores principales:	Jignesh R Parikh, Yu Xia, Jarrod A Marto
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2012
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/a66a4931b9f94c1fad1bf2e168f8d933
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spelling	oai:doaj.org-article:a66a4931b9f94c1fad1bf2e168f8d9332021-11-18T07:05:35ZMulti-edge gene set networks reveal novel insights into global relationships between biological themes.1932-620310.1371/journal.pone.0045211https://doaj.org/article/a66a4931b9f94c1fad1bf2e168f8d9332012-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23028852/?tool=EBIhttps://doaj.org/toc/1932-6203Curated gene sets from databases such as KEGG Pathway and Gene Ontology are often used to systematically organize lists of genes or proteins derived from high-throughput data. However, the information content inherent to some relationships between the interrogated gene sets, such as pathway crosstalk, is often underutilized. A gene set network, where nodes representing individual gene sets such as KEGG pathways are connected to indicate a functional dependency, is well suited to visualize and analyze global gene set relationships. Here we introduce a novel gene set network construction algorithm that integrates gene lists derived from high-throughput experiments with curated gene sets to construct co-enrichment gene set networks. Along with previously described co-membership and linkage algorithms, we apply the co-enrichment algorithm to eight gene set collections to construct integrated multi-evidence gene set networks with multiple edge types connecting gene sets. We demonstrate the utility of approach through examples of novel gene set networks such as the chromosome map co-differential expression gene set network. A total of twenty-four gene set networks are exposed via a web tool called MetaNet, where context-specific multi-edge gene set networks are constructed from enriched gene sets within user-defined gene lists. MetaNet is freely available at http://blaispathways.dfci.harvard.edu/metanet/.Jignesh R ParikhYu XiaJarrod A MartoPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 7, Iss 9, p e45211 (2012)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Jignesh R Parikh Yu Xia Jarrod A Marto Multi-edge gene set networks reveal novel insights into global relationships between biological themes.
description	Curated gene sets from databases such as KEGG Pathway and Gene Ontology are often used to systematically organize lists of genes or proteins derived from high-throughput data. However, the information content inherent to some relationships between the interrogated gene sets, such as pathway crosstalk, is often underutilized. A gene set network, where nodes representing individual gene sets such as KEGG pathways are connected to indicate a functional dependency, is well suited to visualize and analyze global gene set relationships. Here we introduce a novel gene set network construction algorithm that integrates gene lists derived from high-throughput experiments with curated gene sets to construct co-enrichment gene set networks. Along with previously described co-membership and linkage algorithms, we apply the co-enrichment algorithm to eight gene set collections to construct integrated multi-evidence gene set networks with multiple edge types connecting gene sets. We demonstrate the utility of approach through examples of novel gene set networks such as the chromosome map co-differential expression gene set network. A total of twenty-four gene set networks are exposed via a web tool called MetaNet, where context-specific multi-edge gene set networks are constructed from enriched gene sets within user-defined gene lists. MetaNet is freely available at http://blaispathways.dfci.harvard.edu/metanet/.
format	article
author	Jignesh R Parikh Yu Xia Jarrod A Marto
author_facet	Jignesh R Parikh Yu Xia Jarrod A Marto
author_sort	Jignesh R Parikh
title	Multi-edge gene set networks reveal novel insights into global relationships between biological themes.
title_short	Multi-edge gene set networks reveal novel insights into global relationships between biological themes.
title_full	Multi-edge gene set networks reveal novel insights into global relationships between biological themes.
title_fullStr	Multi-edge gene set networks reveal novel insights into global relationships between biological themes.
title_full_unstemmed	Multi-edge gene set networks reveal novel insights into global relationships between biological themes.
title_sort	multi-edge gene set networks reveal novel insights into global relationships between biological themes.
publisher	Public Library of Science (PLoS)
publishDate	2012
url	https://doaj.org/article/a66a4931b9f94c1fad1bf2e168f8d933
work_keys_str_mv	AT jigneshrparikh multiedgegenesetnetworksrevealnovelinsightsintoglobalrelationshipsbetweenbiologicalthemes AT yuxia multiedgegenesetnetworksrevealnovelinsightsintoglobalrelationshipsbetweenbiologicalthemes AT jarrodamarto multiedgegenesetnetworksrevealnovelinsightsintoglobalrelationshipsbetweenbiologicalthemes
_version_	1718423933171007488

Multi-edge gene set networks reveal novel insights into global relationships between biological themes.

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