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Bioinformatics. 2013 Nov 1;29(21):2744-9. doi: 10.1093/bioinformatics/btt477. Epub 2013 Aug 16.

Imputation of coding variants in African Americans: better performance using data from the exome sequencing project.

Author information

1
Department of Genetics and Department of Computer Science, University of North Carolina, Chapel Hill, NC 27599, USA, Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA, Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, USA, Department of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA, Renaissance Computing Institute, University of North Carolina, Chapel Hill, NC 27599, USA, Department of Statistics and Department of Genetics, Rutgers University, Piscataway, NJ 08854, USA, Department of Epidemiology, University of North Carolina, Chapel Hill, NC 27599, USA, Department of Epidemiology, University of Washington, Seattle, WA 98195, USA, Division of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA 15261, USA, Department of Epidemiology and Medicine, University of Iowa, Iowa City, IA 52242, Division of Cardiology, George Washington University School of Medicine and Health Sciences, Washington, DC 20037, USA, Department of Preventive Medicine, Keck School of Medicine, University of Southern California/Norris Comprehensive Cancer Center, Los Angeles, CA 90033, USA, Epidemiology Program, University of Hawaii Cancer Center, HI 96813, USA, Division of Genomic Medicine, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA, Department of Molecular Physiology and Biophysics, Center for Human Genetics Research, Vanderbilt University, Nashville, TN 37232, USA, Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA, Division of Endocrinology, Diabetes and Metabolism, Ohio State University, Columbus, OH 43210, USA, Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, MS 39216, USA and Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA.

Abstract

SUMMARY:

Although the 1000 Genomes haplotypes are the most commonly used reference panel for imputation, medical sequencing projects are generating large alternate sets of sequenced samples. Imputation in African Americans using 3384 haplotypes from the Exome Sequencing Project, compared with 2184 haplotypes from 1000 Genomes Project, increased effective sample size by 8.3-11.4% for coding variants with minor allele frequency <1%. No loss of imputation quality was observed using a panel built from phenotypic extremes. We recommend using haplotypes from Exome Sequencing Project alone or concatenation of the two panels over quality score-based post-imputation selection or IMPUTE2's two-panel combination.

CONTACT:

yunli@med.unc.edu.

SUPPLEMENTARY INFORMATION:

Supplementary data are available at Bioinformatics online.

PMID:
23956302
PMCID:
PMC3799474
DOI:
10.1093/bioinformatics/btt477
[Indexed for MEDLINE]
Free PMC Article

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