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.
journal_name
Nat Genetjournal_title
Nature geneticsauthors
Bulik-Sullivan BK,Loh PR,Finucane HK,Ripke S,Yang J,Schizophrenia Working Group of the Psychiatric Genomics Consortium.,Patterson N,Daly MJ,Price AL,Neale BMdoi
10.1038/ng.3211subject
Has Abstractpub_date
2015-03-01 00:00:00pages
291-5issue
3eissn
1061-4036issn
1546-1718pii
ng.3211journal_volume
47pub_type
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