Eigengene values from a set of gene expression values

Question

Hi

In a gene expression data set (1000s of genes expression values for 100s of samples), I would like to get an eigengene value using values for a specific set of genes for each sample (ie like a gene signature score) — expression values for different genes are in wildly different scales, with some values missing (not detectable - may be imputed with 0).

Is there a way to accomplish this in JMP?

Thanks!

TRR21 · Answer

Genes as columns. Genes to be used haven't been designated in any particular way - was thinking I would specify during the GUI dialog or in the script in order to generate the eigengene/or equivalent for each of the samples (rows). Thanks.

Chris_Kirchberg · Answer

Yes, Hierachical Clustering and PLS (and even PCA for that matter) can help reduce dimentionality of the data (limit the sets of genes) to find or discover set (or sets).

So you already have the sets of genes defined as sets within the data table.  Do you have your genes as rows or columns? How have you desginated the sets of genes in the table?

PCA on the genes (as columns) could be used. For the on Correlations option, the 1st principal component is a linear combination of the centered and scaled observations using the entries of the 1st eigenvector as coefficients.

But what I understrand from how eigengenes were originally calculated, SVD was used.

TRR21 · Answer

Thanks, Chris. As a relative newbie, I am making sure I get this right. I guess hierarchial clustering and PLS are for discovering a novel gene sets? Those are helpful pointers for discovery, but my question was about a predefined set of genes with the whole dataset.

From what I understand, I can just run PCA for my genes of interest, and get the prin1 and this should be analogous to the eigengene value I am looking for?