Package: SIBERG 2.0.3

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:Pan Tong, Kevin R. Coombes

SIBERG_2.0.3.tar.gz
SIBERG_2.0.3.tar.gz(r-4.5-noble)SIBERG_2.0.3.tar.gz(r-4.4-noble)
SIBERG_2.0.3.tgz(r-4.4-emscripten)SIBERG_2.0.3.tgz(r-4.3-emscripten)
SIBERG.pdf |SIBERG.html
SIBERG/json (API)
NEWS

# 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:
  • dataList - Simulated Data From 2-component Mixture Models
  • parList - Simulated Data From 2-component Mixture Models

2.20 score 16 scripts 204 downloads 5 exports 1 dependencies

Last updated 3 years agofrom:e9af1c4eda. Checks:2 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKFeb 18 2025
R-4.5-linuxOKFeb 18 2025

Exports:fitGPfitLNfitNBfitNLSIBER

Dependencies:mclust

SIBER Vignette

Rendered fromSIBER.Rnwusingutils::Sweaveon Feb 18 2025.

Last update: 2018-05-18
Started: 2017-07-11