Package: BayesKnockdown 1.33.0
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_1.33.0.tar.gz
BayesKnockdown_1.33.0.zip(r-4.5)BayesKnockdown_1.33.0.zip(r-4.4)BayesKnockdown_1.33.0.zip(r-4.3)
BayesKnockdown_1.33.0.tgz(r-4.4-any)BayesKnockdown_1.33.0.tgz(r-4.3-any)
BayesKnockdown_1.33.0.tar.gz(r-4.5-noble)BayesKnockdown_1.33.0.tar.gz(r-4.4-noble)
BayesKnockdown_1.33.0.tgz(r-4.4-emscripten)BayesKnockdown_1.33.0.tgz(r-4.3-emscripten)
BayesKnockdown.pdf |BayesKnockdown.html✨
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-1.33.0(bioc 3.21)BayesKnockdown-1.32.0(bioc 3.20)
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
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Last updated 2 months agofrom:ee329ba0ef. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 29 2024 |
| R-4.5-win | OK | Nov 29 2024 |
| R-4.5-linux | OK | Nov 29 2024 |
| R-4.4-win | OK | Nov 29 2024 |
| R-4.4-mac | OK | Nov 29 2024 |
| R-4.3-win | OK | Nov 29 2024 |
| R-4.3-mac | OK | Nov 29 2024 |
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 |