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Estimation of SNP Heritability from Dense Genotype Data

  • Sang Hong Lee
  • , Jian Yang
  • , Naomi R Wray
  • , Guo-Bo Chen
  • , Stephan Ripke
  • , Eli A Stahl
  • , Christina M Hultman
  • , Pamela Sklar
  • , Peter M Visscher
  • , Patrick F Sullivan
  • , Michael E Goddard

Research output: Contribution to journalArticlepeer-review

72 Citations (Scopus)

Abstract

To the Editor: Recently, Speed et al. undertook a comprehensive and elegant evaluation of five key assumptions underlying the linear mixed model implemented in the program GCTA for estimation of SNP heritability. They concluded that the method is robust to violations of four of the assumptions. However, they found that SNP-heritability estimates were sensitive to uneven linkage disequilibrium (LD) between SNPs (implying uneven tagging of causal variants) and suggested an approach to improving the robustness of estimates in this context.
Original languageEnglish
Pages (from-to)1151-1155
JournalAmerican Journal of Human Genetics
Volume93
Issue number6
DOIs
Publication statusPublished - 2013

Keywords

  • Gene Expression (incl. Microarray and other genome-wide approaches)

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