Cross-validation AUC for CLAMP latent variables and pathways

Evaluates how well each latent variable in a CLAMP model captures held-out pathway annotations, using cross-validation over the prior matrix. For each latent variable and associated pathway, held-out genes are selected and the AUC is computed using their scores in clampRes$Z.

crossVal(clampRes, priorMat, priorMatcv)

Arguments

clampRes

A list containing U (loadings) and Z (scores) from a CLAMP model.

priorMat

A binary matrix (genes x pathways) indicating original pathway annotations.

priorMatcv

A version of priorMat used to mask held-out annotations for cross-validation.

Value

A list with:

Uauc

Matrix of AUC values (pathways x LVs)

Upval

Matrix of -log10(p) values (pathways x LVs)

summary

Data frame with pathway, LV index, AUC, p-value, and FDR