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'))

Peer review:

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

5 exports 0.00 score 1 dependencies

Last updated 2 years agofrom:e9af1c4eda4ae766c57d3c92613c7716d3179d30

Exports:fitGPfitLNfitNBfitNLSIBER

Dependencies:mclust

SIBER Vignette

Rendered fromSIBER.Rnwusingutils::Sweaveon May 24 2024.

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