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Characterization of a likelihood based method and effects of markers informativeness in evaluation of admixture and population group assignment

BACKGROUND: Detection and evaluation of population stratification are crucial issues in the conduct of genetic association studies. Statistical approaches useful for understanding these issues have been proposed; these methods rely on information gained from genotyping sets of markers that reflect p...

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Autores principales: Yang, Bao-Zhu, Zhao, Hongyu, Kranzler, Henry R, Gelernter, Joel
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2005
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1285360/
https://www.ncbi.nlm.nih.gov/pubmed/16225681
http://dx.doi.org/10.1186/1471-2156-6-50
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author Yang, Bao-Zhu
Zhao, Hongyu
Kranzler, Henry R
Gelernter, Joel
author_facet Yang, Bao-Zhu
Zhao, Hongyu
Kranzler, Henry R
Gelernter, Joel
author_sort Yang, Bao-Zhu
collection PubMed
description BACKGROUND: Detection and evaluation of population stratification are crucial issues in the conduct of genetic association studies. Statistical approaches useful for understanding these issues have been proposed; these methods rely on information gained from genotyping sets of markers that reflect population ancestry. Before using these methods, a set of markers informative for differentiating population genetic substructure (PGS) is necessary. We have previously evaluated the performance of a Bayesian clustering method implemented in the software STRUCTURE in detecting PGS with a particular informative marker set. In this study, we implemented a likelihood based method (LBM) in evaluating the informativeness of the same selected marker panel, with respect to assessing potential for stratification in samples of European Americans (EAs) and African Americans (AAs), that are known to be admixed. LBM calculates the probability of a set of genotypes based on observations in a reference population with known specific allele frequencies for each marker, assuming Hardy Weinberg equilibrium (HWE) for each marker and linkage equilibrium among markers. RESULTS: In EAs, the assignment accuracy by LBM exceeded 99% using the most efficient marker FY, and reached perfect assignment accuracy using the 10 most efficient markers excluding FY. In AAs, the assignment accuracy reached 96.4% using FY, and >95% when using at least the 9 most efficient markers. The comparison of the observed and reference allele frequencies (which were derived from previous publications and public databases) shows that allele frequencies observed in EAs matched the reference group more accurately than allele frequencies observed in AAs. As a result, the LBM performed better in EAs than AAs, as might be expected given the dependence of LBMs on prior knowledge of allele frequencies. Performance was not dependent on sample size. CONCLUSION: The performance of the LBM depends on the efficiency and number of markers, and depends greatly on how representative the available reference allele frequencies are for those of the population being assigned. This method is of value when the parental population is known and relevant allele frequencies are available.
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spelling pubmed-12853602005-11-19 Characterization of a likelihood based method and effects of markers informativeness in evaluation of admixture and population group assignment Yang, Bao-Zhu Zhao, Hongyu Kranzler, Henry R Gelernter, Joel BMC Genet Research Article BACKGROUND: Detection and evaluation of population stratification are crucial issues in the conduct of genetic association studies. Statistical approaches useful for understanding these issues have been proposed; these methods rely on information gained from genotyping sets of markers that reflect population ancestry. Before using these methods, a set of markers informative for differentiating population genetic substructure (PGS) is necessary. We have previously evaluated the performance of a Bayesian clustering method implemented in the software STRUCTURE in detecting PGS with a particular informative marker set. In this study, we implemented a likelihood based method (LBM) in evaluating the informativeness of the same selected marker panel, with respect to assessing potential for stratification in samples of European Americans (EAs) and African Americans (AAs), that are known to be admixed. LBM calculates the probability of a set of genotypes based on observations in a reference population with known specific allele frequencies for each marker, assuming Hardy Weinberg equilibrium (HWE) for each marker and linkage equilibrium among markers. RESULTS: In EAs, the assignment accuracy by LBM exceeded 99% using the most efficient marker FY, and reached perfect assignment accuracy using the 10 most efficient markers excluding FY. In AAs, the assignment accuracy reached 96.4% using FY, and >95% when using at least the 9 most efficient markers. The comparison of the observed and reference allele frequencies (which were derived from previous publications and public databases) shows that allele frequencies observed in EAs matched the reference group more accurately than allele frequencies observed in AAs. As a result, the LBM performed better in EAs than AAs, as might be expected given the dependence of LBMs on prior knowledge of allele frequencies. Performance was not dependent on sample size. CONCLUSION: The performance of the LBM depends on the efficiency and number of markers, and depends greatly on how representative the available reference allele frequencies are for those of the population being assigned. This method is of value when the parental population is known and relevant allele frequencies are available. BioMed Central 2005-10-14 /pmc/articles/PMC1285360/ /pubmed/16225681 http://dx.doi.org/10.1186/1471-2156-6-50 Text en Copyright © 2005 Yang 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 Research Article
Yang, Bao-Zhu
Zhao, Hongyu
Kranzler, Henry R
Gelernter, Joel
Characterization of a likelihood based method and effects of markers informativeness in evaluation of admixture and population group assignment
title Characterization of a likelihood based method and effects of markers informativeness in evaluation of admixture and population group assignment
title_full Characterization of a likelihood based method and effects of markers informativeness in evaluation of admixture and population group assignment
title_fullStr Characterization of a likelihood based method and effects of markers informativeness in evaluation of admixture and population group assignment
title_full_unstemmed Characterization of a likelihood based method and effects of markers informativeness in evaluation of admixture and population group assignment
title_short Characterization of a likelihood based method and effects of markers informativeness in evaluation of admixture and population group assignment
title_sort characterization of a likelihood based method and effects of markers informativeness in evaluation of admixture and population group assignment
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1285360/
https://www.ncbi.nlm.nih.gov/pubmed/16225681
http://dx.doi.org/10.1186/1471-2156-6-50
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