empirical p-values for glmnet multivariate results

[mschubert]

prerequesites

• map all scores to specific set of pathways
• use same pathway set input for glmnet

kinds of models

• pathways
• mutations and pathways as one input (to compare mut to pathways)
• mutations + pathways (as in, formula syntax - to compare which pathways add most on top)

generation of null models

• null models: 100 repetitions, shuffled labels
• null models: 1000 repetitions, shuffled labels
• real model: one repetition

calc

• empirical p-values for models
• bar plots for best models (as defined with p-val)

[mschubert]

shuffling labels does not introduce enough variability - if e.g. 1 cell line out of 15 is sensitive, will fit in 1/15th of models

will not be a part of the paper, maybe look at this separately