dot-testWass: .testWass

Description Usage Arguments Details Value References


Two-sample test for single-cell RNA-sequencing data to check for differences between two distributions (conditions) using the 2-Wasserstein distance: Semi-parametric implementation using a permutation test with a generalized Pareto distribution (GPD) approximation to estimate small p-values accurately


.testWass(dat, condition, permnum, inclZero = TRUE, seed = NULL)



matrix of single-cell RNA-sequencing expression data with genes in rows and samples (cells) in columns


vector of condition labels


number of permutations used in the permutation testing procedure


logical; if TRUE, the one-stage method (i.e. semi-parametric testing applied to all (zero and non-zero) expression values) is performed; if FALSE, the two-stage method (i.e. semi-parametric testing applied to non-zero expression values only, combined with a separate testing for differential proportions of zero expression using logistic regression) is performed. Default is TRUE


number to be used as a L'Ecuyer-CMRG seed, which itself seeds the generation of an nextRNGStream() for each gene. Internally, when this argument is given, a seed is specified by calling ‘RNGkind("L’Ecuyer-CMRG")' followed by 'set.seed(seed)'. The 'RNGkind' and '.Random.seed' will be reset on termination of this function. By default, NULL is given and no seed is set.


Details concerning the permutation testing procedures for single-cell RNA-sequencing data can be found in Schefzik and Goncalves (2019).


matrix with every row being the wasserstein test of one gene between the two conditions. See the corresponding values in the description of the function, where the argument inclZero=TRUE in .testWass has to be identified with the argument method=<e2><80><9d>OS<e2><80><9d>, and the argument inclZero=FALSE in .testWass with the argument method=<e2><80><9d>TS<e2><80><9d>.


Schefzik and Goncalves 2019

waddR documentation built on Nov. 8, 2020, 8:32 p.m.