Introduction | Using SIBER | Fitting Two-component Mixture Models | Session Info
Package: SIBERG 2.0.4
Kevin R. Coombes
SIBERG: Systematic Identification of Bimodally Expressed Genes Using RNAseq Data
Provides models to identify bimodally expressed genes from RNAseq data based on the Bimodality Index. SIBERG models the RNAseq data in the finite mixture modeling framework and incorporates mechanisms for dealing with RNAseq normalization. Three types of mixture models are implemented, namely, the mixture of log normal, negative binomial, or generalized Poisson distribution. See Tong et al. (2013) <doi:10.1093/bioinformatics/bts713>.
Authors:
SIBERG_2.0.4.tar.gz
SIBERG_2.0.4.tar.gz(r-4.7-any)SIBERG_2.0.4.tar.gz(r-4.6-any)
SIBERG_2.0.4.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
SIBERG/json (API)
| # Install 'SIBERG' in R: |
| install.packages('SIBERG', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://r-forge.r-project.org/projects/oompa
Datasets:
Last updated from:099ff08197. Checks:4 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 112 | ||
| source / vignettes | OK | 165 | ||
| linux-release-x86_64 | OK | 1320 | ||
| wasm-release | OK | 105 |
Exports:fitGPfitLNfitNBfitNLSIBER
Dependencies:mclust
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Fit Generalized Poisson Mixture Model | fitGP |
| Fit Log Normal Mixture Model | fitLN |
| Fit Negative Binomial Mixture Model | fitNB |
| Fit Negative Binomial Mixture Model | fitNL |
| Fit Mixture Model on The RNAseq Data and Calculates Bimodality Index | SIBER |
| Simulated Data From 2-component Mixture Models | dataList parList simDat |