I have a 92,000 columns (genes) x 12 rows (samples) table and would like to use PLS to model treatment effects. However, my treatments (site of origin and temperature) are categorical. If I use discriminant analysis, I can only test one at a time. If I use PLS under the Fit Model platform, I can do a full factorial predictor model, BUT there is no SVD (presumably), so the analysis crashes. Is there something akin to SVD in any PLS-like platform that is NOT discriminant analysis? Alternatively, is it possible to have more than one predictor (X) in the discriminant analysis? I attached the table. Ideally, I would have all 92,960 genes as Y and site of origin, temperature, and their interaction as predictors (3 terms). Maybe my computer is just too old (8 GB RAM with 1.7 Ghz processor)! I am wondering if what I am wanting to do is ONLY achievable with JMP Genomics (which, annoyingly, University of Miami refuses to purchase, even after my nagging!).
One of your options might be one of the penalized regression methods? They don't use SVD, but come at the variable reduction problem from a different analytics point of view...not dimensionality reduction which is baked into PLS. Your computer might still hang because of the number of models that will be 'fit' in the background...but worth a try?
