Gene expression signature (AUC) from gene expression data with 48 +48 samples Does anyone have a good method to find a signature where you combine the expression from multiple genes to predict a specific condition. 
Assume you have performed sequencing of 48 cancer samples and 48 normal sample. Then find a combination of genes that predicts the cancer samples, using for instance AUC.
I have a method for doing this that uses a MCMC algorithm originally designed for population genetics (via the structure program) to generate a statistic between 0 and 1 indicating genetic risk. This needs the use of reference populations for cases and controls that the query individuals are added to for classification. I use T1D as an example. My methods paper is not peer-reviewed, and probably doesn't go into sufficient detail for what you are looking for, but at least indicates one way this can be done:

https://www.biorxiv.org/content/early/2017/01/31/104497

Based on the work I've done with this, using 48 cases and 48 controls with a very specifically defined type of cancer should be sufficient to create a generalised signature from human populations. If a generic cancer profile is needed, the populations are not representative of a general human population, or there are some cases in the control group, then things get trickier and require more individuals. On the other hand, 1500 per group is probably overkill.