Cargando…

GO PaD: the Gene Ontology Partition Database

Gene Ontology (GO) has been widely used to infer functional significance associated with sets of genes in order to automate discoveries within large-scale genetic studies. A level in GO's direct acyclic graph structure is often assumed to be indicative of its terms' specificities, although...

Descripción completa

Detalles Bibliográficos
Autores principales: Alterovitz, Gil, Xiang, Michael, Mohan, Mamta, Ramoni, Marco F.
Formato: Texto
Lenguaje:English
Publicado: Oxford University Press 2007
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1669720/
https://www.ncbi.nlm.nih.gov/pubmed/17098937
http://dx.doi.org/10.1093/nar/gkl799
_version_ 1782131115483463680
author Alterovitz, Gil
Xiang, Michael
Mohan, Mamta
Ramoni, Marco F.
author_facet Alterovitz, Gil
Xiang, Michael
Mohan, Mamta
Ramoni, Marco F.
author_sort Alterovitz, Gil
collection PubMed
description Gene Ontology (GO) has been widely used to infer functional significance associated with sets of genes in order to automate discoveries within large-scale genetic studies. A level in GO's direct acyclic graph structure is often assumed to be indicative of its terms' specificities, although other work has suggested this assumption does not hold. Unfortunately, quantitative analysis of biological functions based on nodes at the same level (as is common in gene enrichment analysis tools) can lead to incorrect conclusions as well as missed discoveries due to inefficient use of available information. This paper addresses these using an informational theoretic approach encoded in the GO Partition Database that guarantees to maximize information for gene enrichment analysis. The GO Partition Database was designed to feature ontology partitions with GO terms of similar specificity. The GO partitions comprise varying numbers of nodes and present relevant information theoretic statistics, so researchers can choose to analyze datasets at arbitrary levels of specificity. The GO Partition Database, featuring GO partition sets for functional analysis of genes from human and 10 other commonly studied organisms with a total of 131 972 genes, is available on the internet at: . The site also includes an online tutorial.
format Text
id pubmed-1669720
institution National Center for Biotechnology Information
language English
publishDate 2007
publisher Oxford University Press
record_format MEDLINE/PubMed
spelling pubmed-16697202007-02-22 GO PaD: the Gene Ontology Partition Database Alterovitz, Gil Xiang, Michael Mohan, Mamta Ramoni, Marco F. Nucleic Acids Res Articles Gene Ontology (GO) has been widely used to infer functional significance associated with sets of genes in order to automate discoveries within large-scale genetic studies. A level in GO's direct acyclic graph structure is often assumed to be indicative of its terms' specificities, although other work has suggested this assumption does not hold. Unfortunately, quantitative analysis of biological functions based on nodes at the same level (as is common in gene enrichment analysis tools) can lead to incorrect conclusions as well as missed discoveries due to inefficient use of available information. This paper addresses these using an informational theoretic approach encoded in the GO Partition Database that guarantees to maximize information for gene enrichment analysis. The GO Partition Database was designed to feature ontology partitions with GO terms of similar specificity. The GO partitions comprise varying numbers of nodes and present relevant information theoretic statistics, so researchers can choose to analyze datasets at arbitrary levels of specificity. The GO Partition Database, featuring GO partition sets for functional analysis of genes from human and 10 other commonly studied organisms with a total of 131 972 genes, is available on the internet at: . The site also includes an online tutorial. Oxford University Press 2007-01 2006-11-10 /pmc/articles/PMC1669720/ /pubmed/17098937 http://dx.doi.org/10.1093/nar/gkl799 Text en © 2006 The Author(s) This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Articles
Alterovitz, Gil
Xiang, Michael
Mohan, Mamta
Ramoni, Marco F.
GO PaD: the Gene Ontology Partition Database
title GO PaD: the Gene Ontology Partition Database
title_full GO PaD: the Gene Ontology Partition Database
title_fullStr GO PaD: the Gene Ontology Partition Database
title_full_unstemmed GO PaD: the Gene Ontology Partition Database
title_short GO PaD: the Gene Ontology Partition Database
title_sort go pad: the gene ontology partition database
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1669720/
https://www.ncbi.nlm.nih.gov/pubmed/17098937
http://dx.doi.org/10.1093/nar/gkl799
work_keys_str_mv AT alterovitzgil gopadthegeneontologypartitiondatabase
AT xiangmichael gopadthegeneontologypartitiondatabase
AT mohanmamta gopadthegeneontologypartitiondatabase
AT ramonimarcof gopadthegeneontologypartitiondatabase