EBSeqHMM-package {EBSeqHMM} | R Documentation

## EBSeqHMM: A Bayesian approach for identifying gene-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 <nleng@wisc.edu>

### 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)

[Package EBSeqHMM version 1.14.0 Index]