Admixture mapping analysis in the context of GWAS with GAW18 data

详细信息    查看全文

• 作者：Mengjie Chen (23)
  Can Yang (24)
  Cong Li (23)
  Lin Hou (24)
  Xiaowei Chen (23)
  Hongyu Zhao (23) (24)
  
• 刊名：BMC Proceedings
• 出版年：2014
• 出版时间：June 2014
• 年：2014
• 卷：8
• 期：1-supp
• 全文大小：240 KB
• 参考文献：1. Reich D, Patterson N, De Jager PL, McDonald GJ, Waliszewska A, Tandon A, Lincoln RR, DeLoa C, Fruhan SA, Cabre P, / et al.: A whole-genome admixture scan finds a candidate locus for multiple sclerosis susceptibility. / Nat Genet 2005, 37:1113鈥?118. CrossRef
  2. Adler S, Pahl M, Abboud H, Nicholas S, Ipp E, Seldin M: Mexican-American admixture mapping analyses for diabetic nephropathy in type 2 diabetes mellitus. / Semin Nephrol 2010, 30:141鈥?49. CrossRef
  3. Alexander DH, Novembre J, Lange K: Fast model-based estimation of ancestry in unrelated individuals. / Genome Res 2009, 19:1655鈥?664. CrossRef
  4. Baran Y, Pasaniuc B, Sankararaman S, Torgerson DG, Gignoux C, Eng C, Rodriguez-Cintron W, Chapela R, Ford JG, Avila PC, / et al.: Fast and accurate inference of local ancestry in Latino populations. / Bioinformatics 2012, 28:1359鈥?367. CrossRef
  5. Churchhouse C, Marchini J: Multi-way admixture deconvolution using phased or unphased ancestral panels. / Genet Epidemiol 2013, 37:1鈥?2. CrossRef
  6. The ALlele FREquency Database [http://alfred.med.yale.edu/alfred/AboutALFRED.asp]
  7. Delaneau O, Marchini J, Zagury JF: A linear complexity phasing method for thousands of genomes. / Nat Methods 2011, 9:179鈥?81. CrossRef
  8. Zhu X, Young JH, Fox E, Keating BJ, Franceschini N, Kang S, Tayo B, Adeyemo A, Sun YV, Li Y, / et al.: Combined admixture mapping and association analysis identifies a novel blood pressure genetic locus on 5p13: contributions from the CARe consortium. / Hum Mol Genet 2011, 20:2285鈥?295. CrossRef
  9. Wang X, Zhu X, Qin H, Cooper RS, Ewens WJ, Li C, Li M: Adjustment for local ancestry in genetic association analysis of admixed populations. / Bioinformatics 2011,27(5):670鈥?77. CrossRef
  
• 作者单位：Mengjie Chen (23)
  Can Yang (24)
  Cong Li (23)
  Lin Hou (24)
  Xiaowei Chen (23)
  Hongyu Zhao (23) (24)
  
  23. Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
  24. Department of Biostatistics, Yale School of Public Health, Yale University, New Haven, CT, 06520, USA
  
• ISSN：1753-6561

文摘

Admixture mapping is a disease-mapping strategy to identify disease susceptibility variants in an admixed population that is a result of mating between 2 historically separated populations differing in allele frequencies and disease prevalence. With the increasing availability of high-density genotyping data generated in genome-wide association studies, it is of interest to investigate how to apply admixture mapping in the context of the genome-wide association studies and how to adjust for admixture in association tests. In this study, we first evaluated 3 different local ancestry inference methods, LAMP, LAMP-LD, and MULTIMIX. Then we applied admixture mapping analysis based on estimated local ancestry. Finally, we performed association tests with adjustment for local ancestry.