distinct: a method for differential analyses via hierarchical permutation tests

distinct is a statistical method to perform differential testing between two or more groups of distributions; differential testing is performed via non-parametric permutation tests on the cumulative distribution functions (cdfs) of each sample. distinct is a general and flexible tool: due to its fully non-parametric nature, which makes no assumptions on how the data was generated, it can be applied to a variety of datasets. It is particularly suitable to perform differential state analyses on single cell data (i.e., differential analyses within sub-populations of cells), such as single cell RNA sequencing (scRNA-seq) and high-dimensional flow or mass cytometry (HDCyto) data.

At present, covariates are not allowed, and only 2-group comparisons are implemented. In future releases (i.e., soon), we will allow for covariates and for differential testing between more than 2 groups.

A pre-print will follow in the coming months.

Bioconductor installation

distinct is available on Bioconductor and can be installed with the command:

if (!requireNamespace("BiocManager", quietly=TRUE))


The vignette illustrating how to use the package can be accessed on the Bioconductor website or from R via:




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distinct documentation built on Nov. 8, 2020, 8:20 p.m.