Abstract:
:Analytical models usually assume an additive sex effect by treating it as a covariate to identify genetic associations with sex-influenced traits. Their underlying assumptions are violated by ignoring interactions of sex with genetic factors and heterogeneous genetic effects by sex. Methods to deal with the problems are compared and discussed in this article. Especially, heterogeneity of genetic variance by sex can be assessed employing a mixed model with genetic relationship matrix constructed from genome-wide nucleotide variant information. Estimating genetic architecture of each sex would help understand different prevalence, course, and severity of complex diseases between women and men in the era of personalized medicine.
journal_name
Curr Genomicsjournal_title
Current genomicsauthors
Lee Cdoi
10.2174/1389202917666160420142601subject
Has Abstractpub_date
2015-10-01 00:00:00pages
439-443issue
5eissn
1389-2029issn
1875-5488pii
CG-17-439journal_volume
17pub_type
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