Utilizing mutual information for detecting rare and common variants associated with a categorical trait.

ABSTRACT: Background. Genome-wide association studies have succeeded in detecting novel common variants which associate with complex diseases. As a result of the fast changes in next generation sequencing technology, a large number of sequencing data are generated, which offers great opportunities to identify rare variants that could explain a larger proportion of missing heritability. Many effective and powerful methods are proposed, although they are usually limited to continuous, dichotomous or ordinal traits. Notice that traits having nominal categorical features are commonly observed in complex diseases, especially in mental disorders, which motivates the incorporation of the characteristics of the categorical trait into association studies with rare and common variants. Methods. We construct t

SUBMITTER: Sun L 

PROVIDER: S-EPMC4918222 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature