I have RNA-seq data from 9 samples and around 15,000 genes. I know that these 9 samples consist of varying proportions of two cell types, each with their own expression profile. I am using non-negative matrix factorization with a rank of 2 to determine the cell-type ratios in each sample. In other words, I use NMF to decompose my 9 x 15,000 matrix into a 2 x 15,000 matrix and a 2 x 9 matrix.
I want to obtain confidence intervals for my estimates of the 2 x 9 matrix. From what I understand about bootstrapping, I could do this by resampling from my 9 observations a bunch of times and keep track of each estimate for each observation.
My question is, since NMF doesn't have any notion of observations vs. features, could I also estimate the variance by resampling genes (features) rather than observations?