Package: BayesKnockdown 1.39.0
William Chad Young
BayesKnockdown: BayesKnockdown: Posterior Probabilities for Edges from Knockdown Data
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.
Authors:
BayesKnockdown_1.39.0.tar.gz
BayesKnockdown_1.39.0.zip(r-4.7)BayesKnockdown_1.39.0.zip(r-4.6)BayesKnockdown_1.39.0.zip(r-4.5)
BayesKnockdown_1.39.0.tgz(r-4.6-any)BayesKnockdown_1.39.0.tgz(r-4.5-any)
BayesKnockdown_1.39.0.tar.gz(r-4.7-any)BayesKnockdown_1.39.0.tar.gz(r-4.6-any)
BayesKnockdown_1.39.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
BayesKnockdown/json (API)
NEWS
| # Install 'BayesKnockdown' in R: |
| install.packages('BayesKnockdown', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
- lincs.kd - LINCS L1000 Knockdown Example Dataset
On BioConductor:BayesKnockdown-1.39.0(bioc 3.24)BayesKnockdown-1.38.0(bioc 3.23)
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
networkinferencegeneexpressiongenetargetnetworkbayesian
Last updated from:26016f1c38. Checks:1 ERROR, 9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| bioc-checks | ERROR | 133 | ||
| linux-devel-x86_64 | OK | 175 | ||
| source / vignettes | OK | 232 | ||
| linux-release-x86_64 | OK | 129 | ||
| macos-release-arm64 | OK | 116 | ||
| macos-oldrel-arm64 | OK | 101 | ||
| windows-devel | OK | 97 | ||
| windows-release | OK | 111 | ||
| windows-oldrel | OK | 63 | ||
| wasm-release | OK | 91 |
Exports:BayesKnockdownBayesKnockdown.diffExpBayesKnockdown.es
Dependencies:BiobaseBiocGenericsgenerics
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Posterior Probabilities for Knockdown Data | BayesKnockdown |
| Posterior Probabilities for 2-class Data | BayesKnockdown.diffExp |
| Posterior Probabilities for ExpressionSet Data | BayesKnockdown.es |
| LINCS L1000 Knockdown Example Dataset | lincs.kd |