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Last data update: 2014.03.03

R: Dimensionality reduction utilities

Dimensionality Reduction

R Documentation

Dimensionality reduction utilities

Description

Dimensionality reduction plots for feature selection and extraction for cummeRbund

Usage

## S4 method for signature 'CuffData'
MDSplot(object,replicates=FALSE,logMode=TRUE,pseudocount=1.0)
## S4 method for signature 'CuffData'
PCAplot(object,x="PC1", y="PC2",replicates=FALSE,pseudocount=1.0,scale=TRUE,showPoints = TRUE,...)

Arguments

`object`	The output of class CuffData from which to draw expression estimates. (e.g. genes(cuff))
`x`	For PCAplot, indicates which principal component is to be presented on the x-axis (e.g. "PC1","PC2","PC3", etc)
`y`	See x.
`pseudocount`	Value added to FPKM to avoid log transformation issues.
`logMode`	Logical value whether or not to use log-transformed expression estimates (default: TRUE)
`replicates`	A logical value to indicate whether or not individual replicate expression estimates will be used.
`scale`	For PCAplot, a logical value passed directly to prcomp.
`showPoints`	For PCAplot, a logical value whether or not to display individual gene values on final PCA plot.
`...`	Additional passthrough arguments (may not be fully implemented yet).

Details

These methods attempt to project a matrix of expression estimates across conditions and/or replicates onto a smaller number of dimesions for feature selection, feature extraction, and can also be useful for outlier detection.

Value

A ggplot2 object.

Note

None.

Author(s)

Loyal A. Goff

References

None.

Examples

	cuff<-readCufflinks(system.file("extdata", package="cummeRbund")) #Create CuffSet object from sample data
	p<-PCAplot(genes(cuff),x="PC2",y="PC3",replicates=TRUE)
	m<-MDSplot(genes(cuff),replicates=TRUE)
	p #Render PCA plot
	m #Render MDS plot

Results


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> library(cummeRbund)
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from 'package:stats':

    IQR, mad, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, cbind, colnames, do.call, duplicated, eval, evalq,
    get, grep, grepl, intersect, is.unsorted, lapply, lengths, mapply,
    match, mget, order, paste, pmax, pmax.int, pmin, pmin.int, rank,
    rbind, rownames, sapply, setdiff, sort, table, tapply, union,
    unique, unsplit

Loading required package: RSQLite
Loading required package: DBI
Loading required package: ggplot2
Loading required package: reshape2
Loading required package: fastcluster

Attaching package: 'fastcluster'

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

    hclust

Loading required package: rtracklayer
Loading required package: GenomicRanges
Loading required package: S4Vectors
Loading required package: stats4

Attaching package: 'S4Vectors'

The following objects are masked from 'package:base':

    colMeans, colSums, expand.grid, rowMeans, rowSums

Loading required package: IRanges
Loading required package: GenomeInfoDb
Loading required package: Gviz
Loading required package: grid

Attaching package: 'cummeRbund'

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

    promoters

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

    promoters

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

    conditions

> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/cummeRbund/dimensionality.Rd_%03d_medium.png", width=480, height=480)
> ### Name: Dimensionality Reduction
> ### Title: Dimensionality reduction utilities
> ### Aliases: MDSplot MDSplot,CuffData-method MDSplot,CuffFeatureSet-method
> ###   PCAplot PCAplot,CuffData-method PCAplot,CuffFeatureSet-method
> 
> ### ** Examples
> 
> 	cuff<-readCufflinks(system.file("extdata", package="cummeRbund")) #Create CuffSet object from sample data
> 	p<-PCAplot(genes(cuff),x="PC2",y="PC3",replicates=TRUE)
> 	m<-MDSplot(genes(cuff),replicates=TRUE)
> 	p #Render PCA plot
> 	m #Render MDS plot
> 	
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>