A Graph-Based Test for Comparing Multivariate Distributions in the Multi Sample Framework

Documentation for package ‘multicross’ version 2.0.0

matchpar	This function takes an scRNAseq counts matrix as an input (cells in rows x genes in cols) and outputs a matrix of cells x 3 covariates (number of genes detected, sequencing depth and mitochondrial gene expression). This covariate matrix can then be used to match cells and perform stratified permutation.
mcm	Multisample generalization of Rosenbaum's crossmatch test
mhcccreate	Creates the null covariance matrix for mmcm, corresponding to the scenario when all K distributions are the same
mhccexecutelong	Calculates the pairwise crosscounts for the K classes being examined
mmcm	Use the Mahalnobis-type multisample test based on optimal matching to compare K different multivariate distributions
multigene	Given two input matrices with the same number of observations but differrent number of variables, this function returns the largest canonical correlation between variables of matrix 1 (X) and those of matrix 2 (Y).
scPath	This function takes an scRNAseq counts matrix as an input (cells in rows x genes in cols) and outputs a list of cells x pathway matrices
select_class	When the MCM/MMCM tests reject the null, class selection can help determine which of the K classes are the likely contributors for rejection
split_mat	Split a data frame or matrix into subsets based on a particular categorical variable