EBSeqHMM-package: EBSeqHMM: A Bayesian approach for identifying gene-expression...

In lengning/EBSeqHMM: Bayesian analysis for identifying gene or isoform expression changes in ordered RNA-seq experiments

Description

The EBSeqHMM package implements an auto-regressive hidden Markov model for statistical analysis in ordered RNA-seq experiments (e.g. time course or spatial course data). The EBSeqHMM package provides functions to identify genes and isoforms that have non-constant expression profile over the time points/positions, and cluster them into expression paths.

Details

Package:	EBSeqHMM
Type:	Package
Version:	0.99.1
Date:	2014-09-16
License:	Artistic-2.0

Author(s)

Ning Leng, Christina Kendziorski Maintainer: Ning Leng <[e-mail]>

References

Leng, N., Li, Y., Mcintosh, B. E., Nguyen, B. K., Duffin, B., Tian, S., Thomson, J. A., Colin, D., Stewart, R. M., and Kendziorski, C. (2014). Ebseq-hmm: A bayesian approach for identifying gene-expression changes in ordered rna-seq experiments.

See Also

EBSeq

Examples

data(GeneExampleData)
CondVector <- rep(paste("t",1:5,sep=""),each=3)
Conditions <- factor(CondVector, levels=c("t1","t2","t3","t4","t5"))
Sizes <- MedianNorm(GeneExampleData)
EBSeqHMMGeneOut <- EBSeqHMMTest(Data=GeneExampleData, sizeFactors=Sizes, Conditions=Conditions,
           UpdateRd=2)

lengning/EBSeqHMM documentation built on May 21, 2019, 4:02 a.m.