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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2017
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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. |
format | Online Article Text |
id | pubmed-5408849 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
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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