lmweber/diffcyt: Differential discovery in high-dimensional cytometry via high-resolution clustering

Statistical methods for differential discovery analyses in high-dimensional cytometry data (including flow cytometry, mass cytometry or CyTOF, and oligonucleotide-tagged cytometry), based on a combination of high-resolution clustering and empirical Bayes moderated tests adapted from transcriptomics.

Getting started

Package details

Bioconductor views CellBasedAssays CellBiology Clustering FeatureExtraction FlowCytometry ImmunoOncology Proteomics SingleCell Software
LicenseMIT + file LICENSE
URL https://github.com/lmweber/diffcyt
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
lmweber/diffcyt documentation built on March 16, 2021, 4:43 p.m.