Searching. Please wait…
1579
37
171
29274
4420
2604
347
391
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.
Fuente: Nature Genetics, 2015, 47(3), 291-295
Publisher: Nature Publishing Group
Year of publication: 2015
No. of pages: 5
Publication type: Article
DOI: 10.1038/ng.3211
ISSN: 1061-4036,1546-1718
Publication Url: https://doi.org/10.1038/ng.3211
Citations in Scopus
Citations in Google Scholar
Other metrics in Scopus
Consult in Scopus
Read publication
RIPKE, S
NEALE, BM
CORVIN, A
WALTERS, JT
FARH, KH
HOLMANS, PA
LEE, P
BULIK-SULLIVAN, B
COLLIER, DA
HUANG, H
PERS, TH
AGARTZ, I
AGERBO, E
ALBUS, M
ALEXANDER, M
AMIN, F
BACANU, SA
BEGEMANN, M
BELLIVEAU, RA
BENE, J
BENEDICTO CRESPO FACORRO
Back