CMImat2matPermu: Permuted Conditional Mutual Information Between Two Matrices

In conMItion: Conditional Mutual Information Estimation for Multi-Omics Data

Permuted Conditional Mutual Information Between Two Matrices

Description

Computes the normalized conditional mutual information (CMI) between vectors sampled from two matrices, conditioned on another vector, normalized by the individual information content. The sampling is done multiple times to generate a distribution.

Usage

CMImat2matPermu(
  mat1,
  mat2,
  condi,
  bin = 6,
  sp_order = 2,
  bulkIdx = 0,
  permutationTimes = 1000,
  seedNum = 99999999
)

Arguments

mat1	A numeric matrix. For example, each row represents a gene and each column represents a sample.
mat2	Another numeric matrix to compare against. Must have the same dimensions as 'mat1'.
condi	A numeric condition vector, matching the number of columns in 'mat1'.
bin	An integer specifying the number of bins. Default is 6.
sp_order	An integer specifying the spline order. Must be less than 'bin'. Default is 2.
bulkIdx	Index to divide the task when processing many permutations. Default is 0.
permutationTimes	Number of permutations for sampling. Default is 1000.
seedNum	Seed for random number generation. Default is 99999999.

Value

A numeric vector of normalized conditional mutual information (CMI) values for each permutation.

Examples

mat1 <- matrix(rnorm(10000), nrow = 100, ncol = 100)
mat2 <- matrix(rnorm(10000), nrow = 100, ncol = 100)
condi <- rnorm(100)
CMImat2matPermu(mat1, mat2, condi)

conMItion documentation built on Aug. 8, 2025, 6:25 p.m.