Bioconductor version: Release (3.14)
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 uw.edu>
Citation (from within R,
enter citation("BayesKnockdown")
):
To install this package, start R (version "4.1") and enter:
if (!require("BiocManager", quietly = TRUE)) install.packages("BiocManager") BiocManager::install("BayesKnockdown")
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:
browseVignettes("BayesKnockdown")
R Script | BayesKnockdown.pdf | |
Reference Manual | ||
Text | NEWS |
biocViews | Bayesian, GeneExpression, GeneTarget, Network, NetworkInference, Software |
Version | 1.20.0 |
In Bioconductor since | BioC 3.4 (R-3.3) (5.5 years) |
License | GPL-3 |
Depends | R (>= 3.3) |
Imports | stats, Biobase |
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Build Report |
Follow Installation instructions to use this package in your R session.
Source Package | BayesKnockdown_1.20.0.tar.gz |
Windows Binary | BayesKnockdown_1.20.0.zip |
macOS 10.13 (High Sierra) | BayesKnockdown_1.20.0.tgz |
Source Repository | git clone https://git.bioconductor.org/packages/BayesKnockdown |
Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/BayesKnockdown |
Package Short Url | https://bioconductor.org/packages/BayesKnockdown/ |
Package Downloads Report | Download Stats |
Old Source Packages for BioC 3.14 | Source Archive |
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