DOI: 10.18129/B9.bioc.cytoMEM  

This package is for version 3.17 of Bioconductor; for the stable, up-to-date release version, see cytoMEM.

Marker Enrichment Modeling (MEM)

Bioconductor version: 3.17

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] , Kirsten Diggins [aut] , Jonathan Irish [aut, cre]

Maintainer: Jonathan Irish < at>

Citation (from within R, enter citation("cytoMEM")):


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biocViews CellBiology, Classification, Clustering, DataImport, DataRepresentation, FlowCytometry, Proteomics, SingleCell, Software, SystemsBiology
Version 1.4.0
In Bioconductor since BioC 3.15 (R-4.2) (1.5 years)
License GPL-3
Depends R (>= 4.2.0)
Imports gplots, tools, flowCore, grDevices, stats, utils, matrixStats, methods
Suggests knitr, rmarkdown
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