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

In 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)

Example output

Loading required package: EBSeq
Loading required package: blockmodeling
To cite package 'blockmodeling' in publications please use package
citation and (at least) one of the articles:

  <U+017D>iberna, Ale<U+0161> (2007). Generalized blockmodeling of valued networks.
  Social Networks 29(1), 105-126.

  <U+017D>iberna, Ale<U+0161> (2008). Direct and indirect approaches to blockmodeling
  of valued networks in terms of regular equivalence. Journal of
  Mathematical Sociology 32(1), 57<U+2013>84.

  ?iberna, Ale? (2018).  Generalized and Classical Blockmodeling of
  Valued Networks, R package version 0.3.4.

To see these entries in BibTeX format, use 'print(<citation>,
bibtex=TRUE)', 'toBibtex(.)', or set
'options(citation.bibtex.max=999)'.
Loading required package: gplots

Attaching package: 'gplots'

The following object is masked from 'package:stats':

    lowess

Loading required package: testthat

Attaching package: 'EBSeqHMM'

The following object is masked from 'package:EBSeq':

    f0


 Conditions are ordered as: 
 t1 t2 t3 t4 t5
 Estimating parameters when expected FC = 2 

 iteration time 0.1 

 iteration time 0 

 iteration time 0.1 

 iteration time 0.1 

 Estimated expected FC 2 

EBSeqHMM documentation built on Nov. 8, 2020, 5:22 p.m.