SIBER: Systematic Identification of Bimodally Expressed Genes Using RNAseq Data

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SIBER(Systematic Identification of Bimodally Expressed genes using RNAseq data) effectively identifies bimodally expressed genes from RNAseq data based on Bimodality Index. SIBER 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.

Author
Pan Tong, Kevin R Coombes
Date of publication
2015-05-26 18:32:12
Maintainer
Pan Tong <nickytong@gmail.com>
License
Apache License (== 2.0)
Version
1.0.0
URLs

View on R-Forge

Man pages

fitGP
Fit Generalized Poisson Mixture Model
fitLN
Fit Log Normal Mixture Model
fitNB
Fit Negative Binomial Mixture Model
fitNL
Fit Negative Binomial Mixture Model
SIBER
Fit Mixture Model on The RNAseq Data and Calculates...
simDat
Simulated Data From 2-component Mixture Models

Files in this package

SIBER/DESCRIPTION
SIBER/NAMESPACE
SIBER/NEWS
SIBER/R
SIBER/R/siberRaw2.R
SIBER/build
SIBER/build/vignette.rds
SIBER/data
SIBER/data/simDat.rda
SIBER/inst
SIBER/inst/doc
SIBER/inst/doc/SIBER.R
SIBER/inst/doc/SIBER.Rnw
SIBER/inst/doc/SIBER.pdf
SIBER/man
SIBER/man/SIBER.Rd
SIBER/man/fitGP.Rd
SIBER/man/fitLN.Rd
SIBER/man/fitNB.Rd
SIBER/man/fitNL.Rd
SIBER/man/simDat.Rd
SIBER/vignettes
SIBER/vignettes/SIBER.Rnw
SIBER/vignettes/siber.bib