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BayesKnockdown: Posterior Probabilities for Edges from Knockdown Data

Bioconductor version: Release (3.18)

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

Maintainer: William Chad Young <wmchad at>

Citation (from within R, enter citation("BayesKnockdown")):


To install this package, start R (version "4.3") and enter:

if (!require("BiocManager", quietly = TRUE))


For older versions of R, please refer to the appropriate Bioconductor release.


To view documentation for the version of this package installed in your system, start R and enter:

BayesKnockdown.pdf PDF R Script
Reference Manual PDF


biocViews Bayesian, GeneExpression, GeneTarget, Network, NetworkInference, Software
Version 1.28.0
In Bioconductor since BioC 3.4 (R-3.3) (7.5 years)
License GPL-3
Depends R (>= 3.3)
Imports stats, Biobase
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Follow Installation instructions to use this package in your R session.

Source Package BayesKnockdown_1.28.0.tar.gz
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macOS Binary (x86_64) BayesKnockdown_1.28.0.tgz
macOS Binary (arm64) BayesKnockdown_1.28.0.tgz
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