SIBER: Systematic Identification of Bimodally Expressed Genes Using RNAseq Data

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.

AuthorPan Tong, Kevin R Coombes
Date of publication2015-05-26 18:32:12
MaintainerPan Tong <nickytong@gmail.com>
LicenseApache License (== 2.0)
Version1.0.0
http://oompa.r-forge.r-project.org/

View on R-Forge

Files

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

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.