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GenFam: A web application and database for gene family‐based classification and functional enrichment analysis

Genome‐scale studies using high‐throughput sequencing (HTS) technologies generate substantial lists of differentially expressed genes under different experimental conditions. These gene lists need to be further mined to narrow down biologically relevant genes and associated functions in order to gui...

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Autores principales: Bedre, Renesh, Mandadi, Kranthi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6892992/
https://www.ncbi.nlm.nih.gov/pubmed/31844835
http://dx.doi.org/10.1002/pld3.191
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author Bedre, Renesh
Mandadi, Kranthi
author_facet Bedre, Renesh
Mandadi, Kranthi
author_sort Bedre, Renesh
collection PubMed
description Genome‐scale studies using high‐throughput sequencing (HTS) technologies generate substantial lists of differentially expressed genes under different experimental conditions. These gene lists need to be further mined to narrow down biologically relevant genes and associated functions in order to guide downstream functional genetic analyses. A popular approach is to determine statistically overrepresented genes in a user‐defined list through enrichment analysis tools, which rely on functional annotations of genes based on Gene Ontology (GO) terms. Here, we propose a new computational approach, GenFam, which allows annotation, classification, and enrichment of genes based on their gene family, thus simplifying identification of candidate gene families and associated genes that may be relevant to the query. GenFam and its integrated database comprises of three hundred and eighty‐four unique gene families and supports gene family analyses for sixty plant genomes. Four comparative case studies with plant species belonging to different clades and families were performed using GenFam which demonstrated its robustness and comprehensiveness over preexisting functional enrichment tools. To make it readily accessible for plant biologists, GenFam is available as a web‐based application where users can input gene IDs and export enrichment results in both tabular and graphical formats. Users can also customize analysis parameters by choosing from the various statistical enrichment tests and multiple testing correction methods. Additionally, the web‐based application, source code, and database are freely available to use and download. Website: http://mandadilab.webfactional.com/home/. Source code and database: http://mandadilab.webfactional.com/home/dload/.
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spelling pubmed-68929922019-12-16 GenFam: A web application and database for gene family‐based classification and functional enrichment analysis Bedre, Renesh Mandadi, Kranthi Plant Direct Original Research Genome‐scale studies using high‐throughput sequencing (HTS) technologies generate substantial lists of differentially expressed genes under different experimental conditions. These gene lists need to be further mined to narrow down biologically relevant genes and associated functions in order to guide downstream functional genetic analyses. A popular approach is to determine statistically overrepresented genes in a user‐defined list through enrichment analysis tools, which rely on functional annotations of genes based on Gene Ontology (GO) terms. Here, we propose a new computational approach, GenFam, which allows annotation, classification, and enrichment of genes based on their gene family, thus simplifying identification of candidate gene families and associated genes that may be relevant to the query. GenFam and its integrated database comprises of three hundred and eighty‐four unique gene families and supports gene family analyses for sixty plant genomes. Four comparative case studies with plant species belonging to different clades and families were performed using GenFam which demonstrated its robustness and comprehensiveness over preexisting functional enrichment tools. To make it readily accessible for plant biologists, GenFam is available as a web‐based application where users can input gene IDs and export enrichment results in both tabular and graphical formats. Users can also customize analysis parameters by choosing from the various statistical enrichment tests and multiple testing correction methods. Additionally, the web‐based application, source code, and database are freely available to use and download. Website: http://mandadilab.webfactional.com/home/. Source code and database: http://mandadilab.webfactional.com/home/dload/. John Wiley and Sons Inc. 2019-12-04 /pmc/articles/PMC6892992/ /pubmed/31844835 http://dx.doi.org/10.1002/pld3.191 Text en © 2019 The Authors. Plant Direct published by American Society of Plant Biologists and the Society for Experimental Biology and John Wiley & Sons Ltd This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Original Research
Bedre, Renesh
Mandadi, Kranthi
GenFam: A web application and database for gene family‐based classification and functional enrichment analysis
title GenFam: A web application and database for gene family‐based classification and functional enrichment analysis
title_full GenFam: A web application and database for gene family‐based classification and functional enrichment analysis
title_fullStr GenFam: A web application and database for gene family‐based classification and functional enrichment analysis
title_full_unstemmed GenFam: A web application and database for gene family‐based classification and functional enrichment analysis
title_short GenFam: A web application and database for gene family‐based classification and functional enrichment analysis
title_sort genfam: a web application and database for gene family‐based classification and functional enrichment analysis
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6892992/
https://www.ncbi.nlm.nih.gov/pubmed/31844835
http://dx.doi.org/10.1002/pld3.191
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