Dimensionality Reduction {cummeRbund} | R Documentation |
Dimensionality reduction plots for feature selection and extraction for cummeRbund
## 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,...)
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). |
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.
A ggplot2 object.
None.
Loyal A. Goff
None.
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