Hi,
I have a question about Principal Component Analysis in R. I have around 10 datasets of interest comprising of both normalized Microarray expression (Agilent, Affymetrix, and Illumina platforms) and RNA-Seq expression (Illumina) data. For each of the dataset, a normalized and corresponding sample metadata (sample grouping information) R.Data file has been saved . I would like to know how to pool and merge all the data and view as a single PCA plot to observe different groups of my interest (i.e Disease vs Control samples). Earlier I have performed PCA on single dataset a time, however, I do not know how to perform pooled PCA analysis. Note: I have both probe-level data and gene level normalized data. All 10 datasets have Disease vs Control samples.
Please assist me with this.
Thank you,
Toufiq
I'm not sure how valid it is to ordinate using different sequencing types, because you might see separation based primarily on method and not on a biologically meaningful differences. But, you could try and see what it looks like I suppose. I would ensure the samples are normalized using the same method (TPM, RPKM, etc),, and then log transform before PCA