exploratory: Methods for Exploratory Analysis in cummeRbund

In gofflab/cummeRbund-BioC-Bridge: Analysis, exploration, manipulation, and visualization of Cufflinks high-throughput sequencing data.

Description

Exploratory analysis methods for cummeRbund RNA-Seq data.

Usage

## S4 method for signature 'CuffData'
csNMF(object,k,logMode=T,pseudocount=1,maxiter=1000,replicates=FALSE,fullnames=FALSE)
## S4 method for signature 'CuffFeatureSet'
csNMF(object,k,logMode=T,pseudocount=1,maxiter=1000,replicates=FALSE,fullnames=FALSE)

Arguments

object	The output of class CuffData or CuffFeatureSet from which to draw expression estimates. (e.g. genes(cuff) or custom feature set via getGenes() or getFeatures() )
k	rank value for factorization
logMode	Logical value whether or not to use log-transformed FPKM values. [Default: TRUE]
pseudocount	Value added to FPKM to avoid log transformation issues.
maxiter	Maximum number of iterations for factorization [Default: 1000]
replicates	A logical value to indicate whether or not individual replicate expression estimates will be used.
fullnames	Logical passthrough value to fpkmMatrix whether or not to concatenate gene_short_name with tracking_id. [Default: FALSE]

Details

csNMF is a convenience method to invoke the nnmf() method from package:NMFN. This performs non-negative matrix factorization on the provided data and can be useful for many downstream applications.

Value

csNMF returns W, H - decomposed matrices of input FPKM values. (See package:NMFN for details)

Note

None.

Author(s)

Loyal A. Goff

References

None.

Examples

	data(sampleData)
	csNMF(sampleGeneSet,4)
	

gofflab/cummeRbund-BioC-Bridge documentation built on May 17, 2019, 7:30 a.m.