make_feature_pair_score_matrix: Combine per sample feature pair score matrices into a single...

In mdkessler/kTSCR: Implements k-Top Scoring Cluster Regression

Description

Combine per sample feature pair score matrices into a single non-redundant matrix (i.e. keep Xi - Xj, but not Xj - Xi, and have scores for every sample in a single matrix)

Usage

make_feature_pair_score_matrix(Is)

Arguments

Is	list of matrices, where each matrix represents a feature x feature score matrix for a single sample

Value

a matrix of feature pair score for each sample

Examples

C <- 100  # represents samples
R <- 200 # represents features
X <- matrix(rbeta(R*C, 2, 3), nrow = R)  # simulate data matrix
Is <- get_pairwise_rank_matrices(X)
pairwise_feature_mat <- make_feature_pair_score_matrix(Is)

mdkessler/kTSCR documentation built on Feb. 25, 2021, 10:31 p.m.