Abstract：
:We consider resequencing studies of associated loci and the problem of prioritizing sequence variants for functional follow-up. Working within the multivariate linear regression framework helps us to account for the joint effects of multiple genes; and adopting a Bayesian approach leads to posterior probabilities that coherently incorporate all information about the variants' function. We describe two novel prior distributions that facilitate learning the role of each variable site by borrowing evidence across phenotypes and across mutations in the same gene. We illustrate their potential advantages with simulations and reanalyzing a data set of sequencing variants.
journal_name
Geneticsjournal_title
Geneticsauthors
Stell L,Sabatti Cdoi
10.1534/genetics.115.184572subject
Has Abstractpub_date
2016-02-01 00:00:00pages
439-55issue
2eissn
0016-6731issn
1943-2631pii
genetics.115.184572journal_volume
202pub_type
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