Literature DB >> 28951529

AdmixPower: Statistical Power and Sample Size Estimation for Mapping Genetic Loci in Admixed Populations.

Yadu Gautam1, Mekibib Altaye2, Changchun Xie3, Tesfaye B Mersha4.   

Abstract

Admixed populations result from recent admixture of two or more ancestral populations with divergent allele frequencies. The genome of each admixed individual is a mosaic of haplotypes inherited from the ancestral populations. Despite the substantial work to assess power and sample size requirements for association mapping in genetically homogeneous populations of European ancestry, power and sample size estimation methods for mapping genes in genetically heterogeneous admixed populations such as African Americans are lacking. Admixture mapping is a method that traces the ancestral origin of disease-susceptibility genetic loci in the admixed population. We developed AdmixPower, a freely available tool set based on the open-source R software, to perform power and sample size analysis for genetically heterogeneous admixed populations considering continuous or dichotomous outcomes with a case-only or case-control study design. AdmixPower can be used to compute the sample size required to achieve investigator-specified statistical power under several key parameters including ancestry odds ratio, genotype risk ratio, parental risk ratio, an underlying genetic risk model, trait type, and admixture model (hybrid-isolation or continuous gene flow model). We demonstrate that differences in the key parameters in the admixed population results in substantial differences in the sample size required to achieve adequate power in admixture mapping studies. Our tool provides a resource for researchers to develop a strategy to minimize cost and maximize the success of identifying disease-susceptibility loci in an admixed population. R code used in the sample size and power analysis is freely available from https://research.cchmc.org/mershalab/Tools.html.
Copyright © 2017 by the Genetics Society of America.

Keywords:  AdmixPower; admixed population; admixture mapping; sample size; statistical power

Mesh:

Year:  2017        PMID: 28951529      PMCID: PMC5676228          DOI: 10.1534/genetics.117.300312

Source DB:  PubMed          Journal:  Genetics        ISSN: 0016-6731            Impact factor:   4.562


  14 in total

1.  Population structure in admixed populations: effect of admixture dynamics on the pattern of linkage disequilibrium.

Authors:  C L Pfaff; E J Parra; C Bonilla; K Hiester; P M McKeigue; M I Kamboh; R G Hutchinson; R E Ferrell; E Boerwinkle; M D Shriver
Journal:  Am J Hum Genet       Date:  2000-12-07       Impact factor: 11.025

2.  Mapping genes that predict treatment outcome in admixed populations.

Authors:  T M Baye; R A Wilke
Journal:  Pharmacogenomics J       Date:  2010-10-05       Impact factor: 3.550

3.  Genetic structure of human populations.

Authors:  Noah A Rosenberg; Jonathan K Pritchard; James L Weber; Howard M Cann; Kenneth K Kidd; Lev A Zhivotovsky; Marcus W Feldman
Journal:  Science       Date:  2002-12-20       Impact factor: 47.728

4.  Genetic Power Calculator: design of linkage and association genetic mapping studies of complex traits.

Authors:  S Purcell; S S Cherny; P C Sham
Journal:  Bioinformatics       Date:  2003-01       Impact factor: 6.937

5.  Linkage analysis of a complex disease through use of admixed populations.

Authors:  Xiaofeng Zhu; Richard S Cooper; Robert C Elston
Journal:  Am J Hum Genet       Date:  2004-05-06       Impact factor: 11.025

6.  Joint analysis is more efficient than replication-based analysis for two-stage genome-wide association studies.

Authors:  Andrew D Skol; Laura J Scott; Gonçalo R Abecasis; Michael Boehnke
Journal:  Nat Genet       Date:  2006-01-15       Impact factor: 38.330

7.  A general population-genetic model for the production by population structure of spurious genotype-phenotype associations in discrete, admixed or spatially distributed populations.

Authors:  Noah A Rosenberg; Magnus Nordborg
Journal:  Genetics       Date:  2006-04-02       Impact factor: 4.562

8.  A genetic atlas of human admixture history.

Authors:  Daniel Falush; Simon Myers; Garrett Hellenthal; George B J Busby; Gavin Band; James F Wilson; Cristian Capelli
Journal:  Science       Date:  2014-02-14       Impact factor: 47.728

9.  GWAPower: a statistical power calculation software for genome-wide association studies with quantitative traits.

Authors:  Sheng Feng; Shengchu Wang; Chia-Cheng Chen; Lan Lan
Journal:  BMC Genet       Date:  2011-01-21       Impact factor: 2.797

Review 10.  Mapping asthma-associated variants in admixed populations.

Authors:  Tesfaye B Mersha
Journal:  Front Genet       Date:  2015-09-29       Impact factor: 4.599

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  4 in total

1.  PAMAM: Power analysis in multiancestry admixture mapping.

Authors:  Yadu Gautam; Sudhir Ghandikota; Siqi Chen; Tesfaye B Mersha
Journal:  Genet Epidemiol       Date:  2019-06-26       Impact factor: 2.135

Review 2.  Genomic Predictors of Asthma Phenotypes and Treatment Response.

Authors:  Natalia Hernandez-Pacheco; Maria Pino-Yanes; Carlos Flores
Journal:  Front Pediatr       Date:  2019-02-05       Impact factor: 3.418

3.  LEI: A Novel Allele Frequency-Based Feature Selection Method for Multi-ancestry Admixed Populations.

Authors:  Michael J Wathen; Yadu Gautam; Sudhir Ghandikota; Marepalli B Rao; Tesfaye B Mersha
Journal:  Sci Rep       Date:  2019-07-31       Impact factor: 4.379

Review 4.  Multi-Omics Profiling Approach to Asthma: An Evolving Paradigm.

Authors:  Yadu Gautam; Elisabet Johansson; Tesfaye B Mersha
Journal:  J Pers Med       Date:  2022-01-07
  4 in total

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