Cargando…
Novel tree-based method to generate markers from rare variant data
Existing methods for analyzing rare variant data focus on collapsing a group of rare variants into a single common variant; collapsing is based on an intuitive function of the rare variant genotype information, such as an indicator function or a weighted sum. It is more natural, however, to take int...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2011
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3287825/ https://www.ncbi.nlm.nih.gov/pubmed/22373418 http://dx.doi.org/10.1186/1753-6561-5-S9-S102 |
_version_ | 1782224752199335936 |
---|---|
author | Jiang, Yuan Brennan, Jennifer S Calixte, Rose He, Yunxiao Nyirabahizi, Epiphanie Zhang, Heping |
author_facet | Jiang, Yuan Brennan, Jennifer S Calixte, Rose He, Yunxiao Nyirabahizi, Epiphanie Zhang, Heping |
author_sort | Jiang, Yuan |
collection | PubMed |
description | Existing methods for analyzing rare variant data focus on collapsing a group of rare variants into a single common variant; collapsing is based on an intuitive function of the rare variant genotype information, such as an indicator function or a weighted sum. It is more natural, however, to take into account the single-nucleotide polymorphism (SNP) interactions informed directly by the data. We propose a novel tree-based method that automatically detects SNP interactions and generates candidate markers from the original pool of rare variants. In addition, we utilize the advantage of having 200 phenotype replications in the Genetic Analysis Workshop 17 data to assess the candidate markers by means of repeated logistic regressions. This new approach shows potential in the rare variant analysis. We correctly identify the association between gene FLT1 and phenotype Affect, although there exist other false positives in our results. Our analyses are performed without knowledge of the underlying simulating model. |
format | Online Article Text |
id | pubmed-3287825 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-32878252012-02-28 Novel tree-based method to generate markers from rare variant data Jiang, Yuan Brennan, Jennifer S Calixte, Rose He, Yunxiao Nyirabahizi, Epiphanie Zhang, Heping BMC Proc Proceedings Existing methods for analyzing rare variant data focus on collapsing a group of rare variants into a single common variant; collapsing is based on an intuitive function of the rare variant genotype information, such as an indicator function or a weighted sum. It is more natural, however, to take into account the single-nucleotide polymorphism (SNP) interactions informed directly by the data. We propose a novel tree-based method that automatically detects SNP interactions and generates candidate markers from the original pool of rare variants. In addition, we utilize the advantage of having 200 phenotype replications in the Genetic Analysis Workshop 17 data to assess the candidate markers by means of repeated logistic regressions. This new approach shows potential in the rare variant analysis. We correctly identify the association between gene FLT1 and phenotype Affect, although there exist other false positives in our results. Our analyses are performed without knowledge of the underlying simulating model. BioMed Central 2011-11-29 /pmc/articles/PMC3287825/ /pubmed/22373418 http://dx.doi.org/10.1186/1753-6561-5-S9-S102 Text en Copyright ©2011 Jiang 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 Jiang, Yuan Brennan, Jennifer S Calixte, Rose He, Yunxiao Nyirabahizi, Epiphanie Zhang, Heping Novel tree-based method to generate markers from rare variant data |
title | Novel tree-based method to generate markers from rare variant data |
title_full | Novel tree-based method to generate markers from rare variant data |
title_fullStr | Novel tree-based method to generate markers from rare variant data |
title_full_unstemmed | Novel tree-based method to generate markers from rare variant data |
title_short | Novel tree-based method to generate markers from rare variant data |
title_sort | novel tree-based method to generate markers from rare variant data |
topic | Proceedings |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3287825/ https://www.ncbi.nlm.nih.gov/pubmed/22373418 http://dx.doi.org/10.1186/1753-6561-5-S9-S102 |
work_keys_str_mv | AT jiangyuan noveltreebasedmethodtogeneratemarkersfromrarevariantdata AT brennanjennifers noveltreebasedmethodtogeneratemarkersfromrarevariantdata AT calixterose noveltreebasedmethodtogeneratemarkersfromrarevariantdata AT heyunxiao noveltreebasedmethodtogeneratemarkersfromrarevariantdata AT nyirabahiziepiphanie noveltreebasedmethodtogeneratemarkersfromrarevariantdata AT zhangheping noveltreebasedmethodtogeneratemarkersfromrarevariantdata |