Package: BayesKnockdown
Title: BayesKnockdown: Posterior Probabilities for Edges from Knockdown
        Data
Version: 1.2.0
Date: 2016-06-28
Author: William Chad Young
Maintainer: William Chad Young <wmchad@uw.edu>
Description: A simple, fast Bayesian method for computing posterior
        probabilities for relationships between a single predictor
        variable and multiple potential outcome variables,
        incorporating prior probabilities of relationships. In the
        context of knockdown experiments, the predictor variable is the
        knocked-down gene, while the other genes are potential targets.
        Can also be used for differential expression/2-class data.
Depends: R (>= 3.3)
Imports: stats, Biobase
License: GPL-3
biocViews: NetworkInference, GeneExpression, GeneTarget, Network,
        Bayesian
LazyData: true
NeedsCompilation: no
Packaged: 2017-04-25 01:32:23 UTC; biocbuild
Built: R 3.4.0; ; 2017-04-25 02:25:57 UTC; windows
