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Identifying genetic variation affecting a complex trait in simulated data: a comparison of meta-analysis with pooled data analysis
We explored the power and consistency to detect linkage and association with meta-analysis and pooled data analysis using Genetic Analysis Workshop 14 simulated data. The first 10 replicates from Aipotu population were used. Significant linkage and association was found at all 4 regions containing t...
Autores principales: | , , , |
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2005
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1866682/ https://www.ncbi.nlm.nih.gov/pubmed/16451713 http://dx.doi.org/10.1186/1471-2156-6-S1-S97 |
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author | Wu, Xiaodong Kan, Donghui Cooper, Richard S Zhu, Xiaofeng |
author_facet | Wu, Xiaodong Kan, Donghui Cooper, Richard S Zhu, Xiaofeng |
author_sort | Wu, Xiaodong |
collection | PubMed |
description | We explored the power and consistency to detect linkage and association with meta-analysis and pooled data analysis using Genetic Analysis Workshop 14 simulated data. The first 10 replicates from Aipotu population were used. Significant linkage and association was found at all 4 regions containing the major loci for Kofendrerd Personality Disorder (KPD) using both combined analyses although no significant linkage and association was found at all these regions in a single replicate. The linkage results from both analyses are consistent in terms of the significance level of linkage test and the estimate of locus location. After correction for multiple-testing, significant associations were detected for the same 8 single-nucleotide polymorphisms (SNP) in both analyses. There were another 2 SNPs for which significant associations with KPD were found only by pooled data analysis. Our study showed that, under homogeneous condition, the results from meta-analysis and pooled data analysis are similar in both linkage and association studies and the loss of power is limited using meta-analysis. Thus, meta-analysis can provide an overall evaluation of linkage and association when the original raw data is not available for combining. |
format | Text |
id | pubmed-1866682 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2005 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-18666822007-05-11 Identifying genetic variation affecting a complex trait in simulated data: a comparison of meta-analysis with pooled data analysis Wu, Xiaodong Kan, Donghui Cooper, Richard S Zhu, Xiaofeng BMC Genet Proceedings We explored the power and consistency to detect linkage and association with meta-analysis and pooled data analysis using Genetic Analysis Workshop 14 simulated data. The first 10 replicates from Aipotu population were used. Significant linkage and association was found at all 4 regions containing the major loci for Kofendrerd Personality Disorder (KPD) using both combined analyses although no significant linkage and association was found at all these regions in a single replicate. The linkage results from both analyses are consistent in terms of the significance level of linkage test and the estimate of locus location. After correction for multiple-testing, significant associations were detected for the same 8 single-nucleotide polymorphisms (SNP) in both analyses. There were another 2 SNPs for which significant associations with KPD were found only by pooled data analysis. Our study showed that, under homogeneous condition, the results from meta-analysis and pooled data analysis are similar in both linkage and association studies and the loss of power is limited using meta-analysis. Thus, meta-analysis can provide an overall evaluation of linkage and association when the original raw data is not available for combining. BioMed Central 2005-12-30 /pmc/articles/PMC1866682/ /pubmed/16451713 http://dx.doi.org/10.1186/1471-2156-6-S1-S97 Text en Copyright © 2005 Wu 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 Wu, Xiaodong Kan, Donghui Cooper, Richard S Zhu, Xiaofeng Identifying genetic variation affecting a complex trait in simulated data: a comparison of meta-analysis with pooled data analysis |
title | Identifying genetic variation affecting a complex trait in simulated data: a comparison of meta-analysis with pooled data analysis |
title_full | Identifying genetic variation affecting a complex trait in simulated data: a comparison of meta-analysis with pooled data analysis |
title_fullStr | Identifying genetic variation affecting a complex trait in simulated data: a comparison of meta-analysis with pooled data analysis |
title_full_unstemmed | Identifying genetic variation affecting a complex trait in simulated data: a comparison of meta-analysis with pooled data analysis |
title_short | Identifying genetic variation affecting a complex trait in simulated data: a comparison of meta-analysis with pooled data analysis |
title_sort | identifying genetic variation affecting a complex trait in simulated data: a comparison of meta-analysis with pooled data analysis |
topic | Proceedings |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1866682/ https://www.ncbi.nlm.nih.gov/pubmed/16451713 http://dx.doi.org/10.1186/1471-2156-6-S1-S97 |
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