This is the released version of cytoMEM; for the devel version, see cytoMEM.
Marker Enrichment Modeling (MEM)Bioconductor version: Release (3.21)
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.
Author: Sierra Lima [aut] ORCID: 0000-0001-5944-750X , Kirsten Diggins [aut] ORCID: 0000-0003-1622-0158 , Jonathan Irish [aut, cre] ORCID: 0000-0001-9428-8866
Maintainer: Jonathan Irish <jonathan.irish at vanderbilt.edu>
Citation (from within R, entercitation("cytoMEM")): Installation
To install this package, start R (version "4.5") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("cytoMEM")
For older versions of R, please refer to the appropriate Bioconductor release.
DocumentationTo view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("cytoMEM")Follow Installation instructions to use this package in your R session.
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