HAPSIMU: a genetic simulation platform for population-based association studies

<p>Abstract</p> <p>Background</p> <p>Population structure is an important cause leading to inconsistent results in population-based association studies (PBAS) of human diseases. Various statistical methods have been proposed to reduce the negative impact of population s...

Full description

Bibliographic Details
Main Authors: Chen Jie, Liu Jianfeng, Zhang Feng, Deng Hong-Wen
Format: Article
Language:English
Published: BMC 2008-08-01
Series:BMC Bioinformatics
Online Access:http://www.biomedcentral.com/1471-2105/9/331
id doaj-c743372bf58e43b98ebd318de99b8dfa
record_format Article
spelling doaj-c743372bf58e43b98ebd318de99b8dfa2020-11-24T21:39:30ZengBMCBMC Bioinformatics1471-21052008-08-019133110.1186/1471-2105-9-331HAPSIMU: a genetic simulation platform for population-based association studiesChen JieLiu JianfengZhang FengDeng Hong-Wen<p>Abstract</p> <p>Background</p> <p>Population structure is an important cause leading to inconsistent results in population-based association studies (PBAS) of human diseases. Various statistical methods have been proposed to reduce the negative impact of population structure on PBAS. Due to lack of structural information in real populations, it is difficult to evaluate the impact of population structure on PBAS in real populations.</p> <p>Results</p> <p>We developed a genetic simulation platform, HAPSIMU, based on real haplotype data from the HapMap ENCODE project. This platform can simulate heterogeneous populations with various known and controllable structures under the continuous migration model or the discrete model. Moreover, both qualitative and quantitative traits can be simulated using additive genetic model with various genetic parameters designated by users.</p> <p>Conclusion</p> <p>HAPSIMU provides a common genetic simulation platform to evaluate the impact of population structure on PBAS, and compare the relative performance of various population structure identification and PBAS methods.</p> http://www.biomedcentral.com/1471-2105/9/331
collection DOAJ
language English
format Article
sources DOAJ
author Chen Jie
Liu Jianfeng
Zhang Feng
Deng Hong-Wen
spellingShingle Chen Jie
Liu Jianfeng
Zhang Feng
Deng Hong-Wen
HAPSIMU: a genetic simulation platform for population-based association studies
BMC Bioinformatics
author_facet Chen Jie
Liu Jianfeng
Zhang Feng
Deng Hong-Wen
author_sort Chen Jie
title HAPSIMU: a genetic simulation platform for population-based association studies
title_short HAPSIMU: a genetic simulation platform for population-based association studies
title_full HAPSIMU: a genetic simulation platform for population-based association studies
title_fullStr HAPSIMU: a genetic simulation platform for population-based association studies
title_full_unstemmed HAPSIMU: a genetic simulation platform for population-based association studies
title_sort hapsimu: a genetic simulation platform for population-based association studies
publisher BMC
series BMC Bioinformatics
issn 1471-2105
publishDate 2008-08-01
description <p>Abstract</p> <p>Background</p> <p>Population structure is an important cause leading to inconsistent results in population-based association studies (PBAS) of human diseases. Various statistical methods have been proposed to reduce the negative impact of population structure on PBAS. Due to lack of structural information in real populations, it is difficult to evaluate the impact of population structure on PBAS in real populations.</p> <p>Results</p> <p>We developed a genetic simulation platform, HAPSIMU, based on real haplotype data from the HapMap ENCODE project. This platform can simulate heterogeneous populations with various known and controllable structures under the continuous migration model or the discrete model. Moreover, both qualitative and quantitative traits can be simulated using additive genetic model with various genetic parameters designated by users.</p> <p>Conclusion</p> <p>HAPSIMU provides a common genetic simulation platform to evaluate the impact of population structure on PBAS, and compare the relative performance of various population structure identification and PBAS methods.</p>
url http://www.biomedcentral.com/1471-2105/9/331
work_keys_str_mv AT chenjie hapsimuageneticsimulationplatformforpopulationbasedassociationstudies
AT liujianfeng hapsimuageneticsimulationplatformforpopulationbasedassociationstudies
AT zhangfeng hapsimuageneticsimulationplatformforpopulationbasedassociationstudies
AT denghongwen hapsimuageneticsimulationplatformforpopulationbasedassociationstudies
_version_ 1725930971424882688