Package: DIRECT 1.1.0
DIRECT: Bayesian Clustering of Multivariate Data Under the Dirichlet-Process Prior
A Bayesian clustering method for replicated time series or replicated measurements from multiple experimental conditions, e.g., time-course gene expression data. It estimates the number of clusters directly from the data using a Dirichlet-process prior. See Fu, A. Q., Russell, S., Bray, S. and Tavare, S. (2013) Bayesian clustering of replicated time-course gene expression data with weak signals. The Annals of Applied Statistics. 7(3) 1334-1361. <doi:10.1214/13-AOAS650>.
Authors:
DIRECT_1.1.0.tar.gz
DIRECT_1.1.0.zip(r-4.5)DIRECT_1.1.0.zip(r-4.4)DIRECT_1.1.0.zip(r-4.3)
DIRECT_1.1.0.tgz(r-4.4-x86_64)DIRECT_1.1.0.tgz(r-4.4-arm64)DIRECT_1.1.0.tgz(r-4.3-x86_64)DIRECT_1.1.0.tgz(r-4.3-arm64)
DIRECT_1.1.0.tar.gz(r-4.5-noble)DIRECT_1.1.0.tar.gz(r-4.4-noble)
DIRECT_1.1.0.tgz(r-4.4-emscripten)DIRECT_1.1.0.tgz(r-4.3-emscripten)
DIRECT.pdf |DIRECT.html✨
DIRECT/json (API)
| # Install 'DIRECT' in R: |
| install.packages('DIRECT', repos = c('https://audreyqyfu.r-universe.dev', 'https://cloud.r-project.org')) |
- tc.data - Time-Course Microarray Gene Expression Data
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 1 years agofrom:de9a9057fc. Checks:OK: 9. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 09 2024 |
| R-4.5-win-x86_64 | OK | Oct 09 2024 |
| R-4.5-linux-x86_64 | OK | Oct 09 2024 |
| R-4.4-win-x86_64 | OK | Oct 09 2024 |
| R-4.4-mac-x86_64 | OK | Oct 09 2024 |
| R-4.4-mac-aarch64 | OK | Oct 09 2024 |
| R-4.3-win-x86_64 | OK | Oct 09 2024 |
| R-4.3-mac-x86_64 | OK | Oct 09 2024 |
| R-4.3-mac-aarch64 | OK | Oct 09 2024 |
Exports:dDirichletDIRECTdMVNormDPMCMCoutputDataplotClustersMeanplotClustersPCAplotClustersSDplotSimulationrDirichletrelabelresampleClusterProbrMVNormsimuDataREMsummaryDIRECT
Dependencies:
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Bayesian Clustering of Multivariate Data with the Dirichlet-Process Prior | DIRECT-package |
| Bayesian Clustering with the Dirichlet-Process Prior | DIRECT direct |
| The Dirichlet Distribution | dDirichlet rDirichlet |
| Dirichlet Process-Based Markov Chain Monte Carlo (MCMC) Sampler for Mixture Model-Based Clustering | DPMCMC |
| The Multivariate Normal Distribution | dMVNorm rMVNorm |
| Writing Simulation Parameters and Data to Files | outputData |
| Plotting Clustered Mean Vectors | plotClustersMean |
| PCA Plot for Posterior Allocation Probability Matrix | plotClustersPCA |
| Plotting Posterior Estimates of Cluster-Specific Random Effects | plotClustersSD |
| Plotting Data Simulated Under A Random-Effects Mixture Model | plotSimulation |
| A Relabel Algorithm | relabel |
| Resampling to Estimate Posterior Allocation Probability Matrix | resampleClusterProb |
| Data Simulation Under the Random-Effects Mixture Model | simuDataREM |
| Processing Posterior Estimates for Clustering Under DIRECT | summaryDIRECT |
| Time-Course Microarray Gene Expression Data | tc.data |
