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
Browse package contents
Package details |
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| Bioconductor views | CellBasedAssays CellBiology Clustering FeatureExtraction FlowCytometry ImmunoOncology Proteomics SingleCell Software |
| Maintainer | |
| License | MIT + file LICENSE |
| Version | 1.23.1 |
| URL | https://github.com/lmweber/diffcyt |
| Package repository | View on GitHub |
| Installation |
Install the latest version of this package by entering the following in R:
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