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

نویسندگان

  • Qing Duan
  • Eric Yi Liu
  • Paul L. Auer
  • Guosheng Zhang
  • Ethan M. Lange
  • Goo Jun
  • Chris Bizon
  • Shuo Jiao
  • Steven Buyske
  • Nora Franceschini
  • Chris S. Carlson
  • Li Hsu
  • Alex P. Reiner
  • Ulrike Peters
  • Jeffrey Haessler
  • Keith Curtis
  • Christina L. Wassel
  • Jennifer G. Robinson
  • Lisa W. Martin
  • Christopher A. Haiman
  • Loic Le Marchand
  • Tara Cox Matise
  • Lucia A. Hindorff
  • Dana C. Crawford
  • Themistocles L. Assimes
  • Hyun Min Kang
  • Gerardo Heiss
  • Rebecca D. Jackson
  • Charles Kooperberg
  • James G. Wilson
  • Gonçalo R. Abecasis
  • Kari E. North
  • Deborah A. Nickerson
  • Leslie A. Lange
  • Yun Li
چکیده

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 [email protected]. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.

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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 vari...

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عنوان ژورنال:
  • Bioinformatics

دوره 29 21  شماره 

صفحات  -

تاریخ انتشار 2013