Hello,
I am working on edgeR version 3.2.3.
From the documentation, I guess the "plotMDS.DGEList" is similar to PCA. The manual mentions that "Distances on the plot represent coefficient of variation of expression between samples".
Is it possible to get a value of proportion of variance explained from each dimension (component)? Also, is it possible to use the DGEList to make a 3D PCA plot?
Thanks,
Manoj.
Manoj Hariharan
Staff Researcher
The Salk Institute for Biological Studies
La Jolla, CA 92037
Office: 858.453.4100 x2143
Dear Gordon,
I was always wondering about the same question since I am not a statistician. What I found reading on the internet is that MDS uses distances to calculate eigenvectors, so you can do MDS although you do not know the absolute coordinates but using the relative distances. But if you have the original values, then standard Principal Component Analysis and classical (metric) MDS should give the same components. But please correct me if I am wrong. That would explain why plotMDS and PCA score plots are that often that similar when used with limma.
Thanks for the posts.
Jose
Dear Jose,
The plotMDS() limma function doesn't compute classical Euclidean distances, not by default anyway.
Cheers
Gordon