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MEGA-V: detection of variant gene sets in patient cohorts

SUMMARY: Detecting significant associations between genetic variants and disease may prove particularly challenging when the variants are rare in the population and/or act together with other variants to cause the disease. We have developed a statistical framework named Mutation Enrichment Gene set...

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Autores principales: Gambardella, Gennaro, Cereda, Matteo, Benedetti, Lorena, Ciccarelli, Francesca D
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5408849/
https://www.ncbi.nlm.nih.gov/pubmed/28003259
http://dx.doi.org/10.1093/bioinformatics/btw809
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author Gambardella, Gennaro
Cereda, Matteo
Benedetti, Lorena
Ciccarelli, Francesca D
author_facet Gambardella, Gennaro
Cereda, Matteo
Benedetti, Lorena
Ciccarelli, Francesca D
author_sort Gambardella, Gennaro
collection PubMed
description SUMMARY: Detecting significant associations between genetic variants and disease may prove particularly challenging when the variants are rare in the population and/or act together with other variants to cause the disease. We have developed a statistical framework named Mutation Enrichment Gene set Analysis of Variants (MEGA-V) that specifically detects the enrichments of genetic alterations within a process in a cohort of interest. By focusing on the mutations of several genes contributing to the same function rather than on those affecting a single gene, MEGA-V increases the power to detect statistically significant associations. AVAILABILITY AND IMPLEMENTATION: MEGA-V is available at https://github.com/ciccalab/MEGA SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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spelling pubmed-54088492017-05-03 MEGA-V: detection of variant gene sets in patient cohorts Gambardella, Gennaro Cereda, Matteo Benedetti, Lorena Ciccarelli, Francesca D Bioinformatics Applications Notes SUMMARY: Detecting significant associations between genetic variants and disease may prove particularly challenging when the variants are rare in the population and/or act together with other variants to cause the disease. We have developed a statistical framework named Mutation Enrichment Gene set Analysis of Variants (MEGA-V) that specifically detects the enrichments of genetic alterations within a process in a cohort of interest. By focusing on the mutations of several genes contributing to the same function rather than on those affecting a single gene, MEGA-V increases the power to detect statistically significant associations. AVAILABILITY AND IMPLEMENTATION: MEGA-V is available at https://github.com/ciccalab/MEGA SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2017-04-15 2016-12-21 /pmc/articles/PMC5408849/ /pubmed/28003259 http://dx.doi.org/10.1093/bioinformatics/btw809 Text en © The Author 2016. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Applications Notes
Gambardella, Gennaro
Cereda, Matteo
Benedetti, Lorena
Ciccarelli, Francesca D
MEGA-V: detection of variant gene sets in patient cohorts
title MEGA-V: detection of variant gene sets in patient cohorts
title_full MEGA-V: detection of variant gene sets in patient cohorts
title_fullStr MEGA-V: detection of variant gene sets in patient cohorts
title_full_unstemmed MEGA-V: detection of variant gene sets in patient cohorts
title_short MEGA-V: detection of variant gene sets in patient cohorts
title_sort mega-v: detection of variant gene sets in patient cohorts
topic Applications Notes
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5408849/
https://www.ncbi.nlm.nih.gov/pubmed/28003259
http://dx.doi.org/10.1093/bioinformatics/btw809
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