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Molecular Physiology & Biophysics

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

AUTHORS

Duan Q , Liu EY , Auer PL , Zhang G , Lange EM , Jun G , Bizon C , Jiao S , Buyske S , Franceschini N , Carlson CS , Hsu L , Reiner AP , Peters U , Haessler J , Curtis K , Wassel CL , Robinson JG , Martin LW , Haiman CA , Le Marchand L , Matise TC , Hindorff LA , Crawford DC , Assimes TL , Kang HM , Heiss G , Jackson RD , Kooperberg C , Wilson JG , Abecasis GR , North KE , Nickerson DA , Lange LA , Li Y , . Bioinformatics (Oxford, England). 2013 11 1; 29(21). 2744-9

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.

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.

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