Abstract:
:We present a new statistical test of association between a trait and genetic markers, which we theoretically and practically prove to be robust to arbitrarily complex population structure. The statistical test involves a set of parameters that can be directly estimated from large-scale genotyping data, such as those measured in genome-wide association studies (GWAS). We also derive a new set of methodologies, called a 'genotype-conditional association test' (GCAT), shown to provide accurate association tests in populations with complex structures, manifested in both the genetic and non-genetic contributions to the trait. We demonstrate the proposed method on a large simulation study and on the Northern Finland Birth Cohort study. In the Finland study, we identify several new significant loci that other methods do not detect. Our proposed framework provides a substantially different approach to the problem from existing methods, such as the linear mixed-model and principal-component approaches.
journal_name
Nat Genetjournal_title
Nature geneticsauthors
Song M,Hao W,Storey JDdoi
10.1038/ng.3244subject
Has Abstractpub_date
2015-05-01 00:00:00pages
550-4issue
5eissn
1061-4036issn
1546-1718pii
ng.3244journal_volume
47pub_type
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