cytolab/cytoMEM: Marker Enrichment Modeling (MEM)

MEM, Marker Enrichment Modeling, automatically generates and displays quantitative labels for cell populations that have been identified from single-cell data. The input for MEM is a dataset that has pre-clustered or pre-gated populations with cells in rows and features in columns. Labels convey a list of measured features and the features' levels of relative enrichment on each population. MEM can be applied to a wide variety of data types and can compare between MEM labels from flow cytometry, mass cytometry, single cell RNA-seq, and spectral flow cytometry using RMSD.

Getting started

Package details

Bioconductor views CellBiology Classification Clustering DataImport DataRepresentation FlowCytometry Proteomics SingleCell SystemsBiology
Maintainer
LicenseGPL-3
Version0.99.2
URL https://github.com/cytolab/cytoMEM
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("cytolab/cytoMEM")
cytolab/cytoMEM documentation built on Sept. 13, 2023, 7:28 a.m.