Cargando…
A pathway-based association analysis model using common and rare variants
How various genetic effects in combination affect susceptibility to certain disease states continues to be a major area of methodological research. Various rare variant models have been proposed, in response to a common failure to either identify or validate biologically driven causal genetic varian...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2011
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3287926/ https://www.ncbi.nlm.nih.gov/pubmed/22373433 http://dx.doi.org/10.1186/1753-6561-5-S9-S85 |
_version_ | 1782224775177830400 |
---|---|
author | Cheng, Lu Hu, Pingzhao Sykes, Jenna Pintilie, Melania Liu, Geoffrey Xu, Wei |
author_facet | Cheng, Lu Hu, Pingzhao Sykes, Jenna Pintilie, Melania Liu, Geoffrey Xu, Wei |
author_sort | Cheng, Lu |
collection | PubMed |
description | How various genetic effects in combination affect susceptibility to certain disease states continues to be a major area of methodological research. Various rare variant models have been proposed, in response to a common failure to either identify or validate biologically driven causal genetic variants in genome-wide association studies. Adopting the idea that multiple rare variants may effectively produce a combined effect equal to a single common variant effect through common linkage with this variant, we construct a pathway-based genetic association analysis model using both common and rare variants. This genetic model is applied to the disease status of unrelated individuals in replication 1 from Genetic Analysis Workshop 17. In this simulated example, we were able to identify several pathways that were potentially associated with the disease status and found that common variants showed stronger genetic effect than rare variants. |
format | Online Article Text |
id | pubmed-3287926 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-32879262012-02-28 A pathway-based association analysis model using common and rare variants Cheng, Lu Hu, Pingzhao Sykes, Jenna Pintilie, Melania Liu, Geoffrey Xu, Wei BMC Proc Proceedings How various genetic effects in combination affect susceptibility to certain disease states continues to be a major area of methodological research. Various rare variant models have been proposed, in response to a common failure to either identify or validate biologically driven causal genetic variants in genome-wide association studies. Adopting the idea that multiple rare variants may effectively produce a combined effect equal to a single common variant effect through common linkage with this variant, we construct a pathway-based genetic association analysis model using both common and rare variants. This genetic model is applied to the disease status of unrelated individuals in replication 1 from Genetic Analysis Workshop 17. In this simulated example, we were able to identify several pathways that were potentially associated with the disease status and found that common variants showed stronger genetic effect than rare variants. BioMed Central 2011-11-29 /pmc/articles/PMC3287926/ /pubmed/22373433 http://dx.doi.org/10.1186/1753-6561-5-S9-S85 Text en Copyright ©2011 Cheng et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Proceedings Cheng, Lu Hu, Pingzhao Sykes, Jenna Pintilie, Melania Liu, Geoffrey Xu, Wei A pathway-based association analysis model using common and rare variants |
title | A pathway-based association analysis model using common and rare variants |
title_full | A pathway-based association analysis model using common and rare variants |
title_fullStr | A pathway-based association analysis model using common and rare variants |
title_full_unstemmed | A pathway-based association analysis model using common and rare variants |
title_short | A pathway-based association analysis model using common and rare variants |
title_sort | pathway-based association analysis model using common and rare variants |
topic | Proceedings |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3287926/ https://www.ncbi.nlm.nih.gov/pubmed/22373433 http://dx.doi.org/10.1186/1753-6561-5-S9-S85 |
work_keys_str_mv | AT chenglu apathwaybasedassociationanalysismodelusingcommonandrarevariants AT hupingzhao apathwaybasedassociationanalysismodelusingcommonandrarevariants AT sykesjenna apathwaybasedassociationanalysismodelusingcommonandrarevariants AT pintiliemelania apathwaybasedassociationanalysismodelusingcommonandrarevariants AT liugeoffrey apathwaybasedassociationanalysismodelusingcommonandrarevariants AT xuwei apathwaybasedassociationanalysismodelusingcommonandrarevariants AT chenglu pathwaybasedassociationanalysismodelusingcommonandrarevariants AT hupingzhao pathwaybasedassociationanalysismodelusingcommonandrarevariants AT sykesjenna pathwaybasedassociationanalysismodelusingcommonandrarevariants AT pintiliemelania pathwaybasedassociationanalysismodelusingcommonandrarevariants AT liugeoffrey pathwaybasedassociationanalysismodelusingcommonandrarevariants AT xuwei pathwaybasedassociationanalysismodelusingcommonandrarevariants |