Local and global ancestry inference and applications to genetic association analysis for admixed Populations

Genetic Epidemiology

Volumn 38, Issue SUPPL.1, 2014, Pages

  Thornton, Timothy A ^a   Bermejo, Justo Lorenzo ^b  

^a UNIVERSITY OF WASHINGTON   (United States)

^b UNIVERSITY OF HEIDELBERG   (Germany)

Author keywords

Admixture; Association; Genotype imputation; GWAS; Local ancestry

Indexed keywords

SPACER DNA;

AMERICAN INDIAN; ARTICLE; CHROMOSOME 3; DIASTOLIC BLOOD PRESSURE; GENE MAPPING; GENE SEQUENCE; GENETIC ANALYSIS; GENETIC ASSOCIATION; GENETIC HETEROGENEITY; GENETIC VARIABILITY; GENOTYPE; HAPLOTYPE MAP; HUMAN; HYPERTENSION; MAJOR CLINICAL STUDY; MEXICAN AMERICAN; PEDIGREE; PHENOTYPE; POPULATION GENETICS; POPULATION STRUCTURE; SINGLE NUCLEOTIDE POLYMORPHISM; SYSTOLIC BLOOD PRESSURE;

ADMIXTURE; ASSOCIATION; GENOTYPE IMPUTATION; GWAS; LOCAL ANCESTRY;

BLOOD PRESSURE; CHROMOSOME MAPPING; GENETIC ASSOCIATION STUDIES; GENETIC HETEROGENEITY; GENETICS, POPULATION; GENOTYPE; HUMANS; MEXICAN AMERICANS; PEDIGREE; POLYMORPHISM, SINGLE NUCLEOTIDE; PRINCIPAL COMPONENT ANALYSIS; SEQUENCE ANALYSIS, DNA;

EID: 84905682433     PISSN: 07410395     EISSN: 10982272     Source Type: Journal    
DOI: 10.1002/gepi.21819     Document Type: Article

References (28)

1. 1000 Genomes Project Consortium. 2010. A map of human genome variation from population-scale sequencing. Nature 467:1061-1073.
2. Alexander DH, Novembre J, Lange K. 2009. Fast model-based estimation of ancestry in unrelated individuals. Genome Res 19:1655-1664.
3. Almasy L, Dyer TD, Peralta JM, Jun G, Wood AR, Fuchsberger C, Almeida MA, Kent JW Jr, Fowler S, Blackwell TW and others 2014. Data for Genetic Analysis Workshop 18: human whole-genome sequence, blood pressure, and simulated phenotypes in extended pedigrees. BMC Proc 8(Suppl 1):S2.
4. Baran Y, Pasaniuc B, Sankararaman S, Torgerson GD, Gignoux C, Eng C, Rodriguez-Cintron W, Chapela R, Ford JG, Avila PC and others 2012. Fast and accurate inference of local ancestry in Latino populations. Bioinformatics 28:1359-1367.
5. Chen M, Yang C, Li C, Hou L, Chen X, Zhao H. 2014. Admixture mapping analysis in the context of GWAS with GAW18 data. BMC Proc 8(Suppl 1):S3.
6. Churchhouse C, Marchini J. 2013. Multi-way admixture deconvolution using phased or unphased ancestral panels. Genet Epidemiol 37:1-12.
7. Culverhouse RC, Hinrichs AL, Suarez BK. 2014. Identifying cryptic population structure in multigeneration pedigrees in a Mexican American sample. BMC Proc 8(Suppl 1):S4.
8. Devlin B, Roeder K. 1999. Genomic control for association studies. Biometrics 55:997-1004.
9. Genovese G, Handsaker RE, Li H, Altemose N, Lindgren AM, Chambert K, Pasaniuc B, Price AL, Reich D, Morton CC and others 2013. Using population admixture to help complete maps of the human genome. Nat Genet 45:406-414.
10. Hancock DB, Levy JL, Gaddis NC, Bierut LJ, Saccone NL, Page GP, Johnson EO. 2012. Assessment of genotype imputation performance using 1000 Genomes in African American studies. PLoS One 7:e50610.
11. Howie B, Fuchsberger C, Stephens M, Marchini J, Abecasis GR. 2012. Fast and accurate genotype imputation in genome-wide association studies through prephasing. Nat Genet 44:955-959.
12. Howie BN, Donnelly P, Marchini J. 2009. A flexible and accurate genotype imputation method for the next generation of genome-wide association studies. PLoS Genet 5:e1000529.
13. Huang GH, Tseng YC. 2014. Genotype imputation accuracy with different reference panels in admixed populations. BMC Proc 8(Suppl 1):S64.
14. International HapMap 3 Consortium. 2010. Integrating common and rare genetic variation in diverse human populations. Nature 467:52-58.
15. Johnson NA, Coram MA, Shriver MD, Romieu I, Barsh GS, London SJ, Tang H. 2011. Ancestral components of admixed genomes in a Mexican cohort. PLoS Genet 7:e1002410.
16. Kang HM, Sul JH, Service SK, Zaitlen NA, Kong SY, Freimer NB, Sabatti C, Eskin E. 2010. Variance component model to account for sample structure in genome-wide association studies. Nat Genet 42:348-354.
17. Li JZ, Absher DM, Tang H, Southwick AM, Casto AM, Ramachandran S, Cann HM, Barsh GS, Feldman M, Cavalli-Sforza LL and others 2008. Worldwide human relationships inferred from genome-wide patterns of variation. Science 319:1100-1104.
18. Li Y, Willer CJ, Ding J, Scheet P, Abecasis GR. 2010. MACH: using sequence and genotype data to estimate haplotypes and unobserved genotypes. Genet Epidemiol 34:816-834.
19. Manichaikul A, Palmas W, Rodriguez CJ, Peralta CA, Divers J, Guo X, Chen WM, Wong Q, Williams K, Kerr KF and others 2012. Population structure of Hispanics in the United States: the multi-ethnic study of atherosclerosis. PLoS Genet 8:e1002640.
20. Price AL, Patterson NH, Plenge RM, Weinblatt ME, Shadick NA, Reich D. 2006. Principal components analysis corrects for stratification in genome-wide association studies. Nat Genet 38:904-909.
21. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MAR, Bender D, Maller J, Sklar P, de Bakker PI, Daly MJ and others 2007. PLINK: a tool set for whole-genome association and population-based linkage analysis. Am J Hum Genet 81:559-575.
22. Sankararaman S, Sridhar S, Kimmel G, Halperin E. 2008. Estimating local ancestry in admixed populations. Am J Hum Genet 82:290-303.
23. Scheet P, Stephens M. 2006. A fast and flexible statistical model for large-scale population genotype data: applications to inferring missing genotypes and haplotypic phase. Am J Hum Genet 78:629-644.
24. Tang H, Peng J, Wang P, Risch NJ. 2005. Estimation of individual admixture: analytical and study design considerations. Genet Epidemiol 28:289-301.
25. Thornton T, Tang H, Hoffman TJ, Ochs-Balcom HM, Baan BJ, Risch NJ. 2012. Estimating kinship in admixed populations. Am J Hum Genet 91:122-138.
26. Thornton T, Conomos M, Sverdlov S, Blue EM, Cheung C, Glazner C, Lewis S, Wijsman EM. 2014. Estimating and adjusting for ancestry admixture in statistical methods for relatedness inference, heritability estimation, and association testing. BMC Proc 8(Suppl 1):S5.
27. Yorgov D, Edwards KL, Santorico SA. 2014. Use of admixture and association for detection of quantitative trait loci in the type 2 diabetes genetic exploration by next-generation sequencing in ethnic samples (T2D-GENES) study. BMC Proc 8(Suppl 1):S6.
28. Zhu X, Li S, Cooper RS, Elston RC. 2008. A unified association analysis approach for family and unrelated samples correcting for stratification. Am J Hum Genet 82:352-365.