[BioC] how to use principal component analysis in R

[Aedin]

Dear Weinong,
We have provided a simple package for running PCA or correspondence
analysis in the bioconductor package made4.
It will accept most bioconductor data classes, a matrix or data.frame.
To run a PCA

library(made4)
res<-ord(data, "pca")
plot(res)

This will give a plot of the eigenvalues, and the first two eigenvectors
of the cases (arrays) and genes.  Only the genes at the ends of the axes
are labelled (to ease the visualisation). You can also use

plotarrays(res)
plotgenes(res)

To visualise the genes and arrays.

The package made4 required that ade4 is installed. If this is not, you
can install it using
install.packages("ade4")


Regards
Aedin





>>> weinong han <hanweinong at yahoo.com> 06/18/05 2:10 AM >>>
Dear All,
 
Wish you have a nice weekend.
 
I want to run the two-dimensional principal-components analysis of
patient group using 174-gene signature  set  from Welch-T test to
separate the patient group, at the same time, I want to the plots of PCA
results.
 
Anyone tried or not? please tell me the functions and scripts.
 
Any advice and suggestions will be much appreciated.
 
Thanks in advance.


Best Regards
 
Han Weinong  
hanweinong at yahoo.com