LD score regression distinguishes confounding from polygenicity in genome-wide association studies

Schizophrenia Working Group of the Psychiatric Genomics Consortium

研究成果: Article査読

1208 被引用数 (Scopus)

抄録

Both polygenicity (many small genetic effects) and confounding biases, such as cryptic relatedness and population stratification, can yield an inflated distribution of test statistics in genome-wide association studies (GWAS). However, current methods cannot distinguish between inflation from a true polygenic signal and bias. We have developed an approach, LD Score regression, that quantifies the contribution of each by examining the relationship between test statistics and linkage disequilibrium (LD). The LD Score regression intercept can be used to estimate a more powerful and accurate correction factor than genomic control. We find strong evidence that polygenicity accounts for the majority of the inflation in test statistics in many GWAS of large sample size.

本文言語English
ページ(範囲)291-295
ページ数5
ジャーナルNature Genetics
47
3
DOI
出版ステータスPublished - 25-02-2015

All Science Journal Classification (ASJC) codes

  • Genetics

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