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.
Package details |
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Bioconductor views | CellBiology Classification Clustering DataImport DataRepresentation FlowCytometry Proteomics SingleCell SystemsBiology |
Maintainer | |
License | GPL-3 |
Version | 0.99.2 |
URL | https://github.com/cytolab/cytoMEM |
Package repository | View on GitHub |
Installation |
Install the latest version of this package by entering the following in R:
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