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.

Package details

AuthorLukas M. Weber [aut, cre] (<https://orcid.org/0000-0002-3282-1730>)
Bioconductor views CellBasedAssays CellBiology Clustering FeatureExtraction FlowCytometry ImmunoOncology Proteomics SingleCell Software
MaintainerLukas M. Weber <lukas.weber.edu@gmail.com>
LicenseMIT + file LICENSE
URL https://github.com/lmweber/diffcyt
Package repositoryView on Bioconductor
Installation Install the latest version of this package by entering the following in R:
if (!requireNamespace("BiocManager", quietly = TRUE))


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diffcyt documentation built on Nov. 8, 2020, 6:37 p.m.