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.
|Author||William Chad Young|
|Bioconductor views||Bayesian GeneExpression GeneTarget Network NetworkInference|
|Maintainer||William Chad Young <[email protected]>|
|Package repository||View on GitHub|
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