Publication Date
2015
Journal Title
Nat Genet
Abstract
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.
Volume Number
47
Issue Number
3
Pages
291-5
Document Type
Article
EPub Date
2015/02/03
Status
Faculty
Facility
School of Medicine
Primary Department
Psychiatry
Additional Departments
Molecular Medicine
PMID
DOI
10.1038/ng.3211