This site is a development preview. As such the content and styling may not be final and is subject to change before going into production. To see more information about the redesign click here.

cytoMEM

This is the development version of cytoMEM; for the stable release version, see cytoMEM.

Marker Enrichment Modeling (MEM)

Bioconductor version: Development (3.18)

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 <jonathan.irish at vanderbilt.edu>

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

Installation

To install this package, start R (version "4.3") and enter:

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

BiocManager::install("cytoMEM")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("cytoMEM")
Intro_to_Marker_Enrichment_Modeling_Analysis HTML R Script
Reference Manual PDF
NEWS Text

Details

biocViews CellBiology, Classification, Clustering, DataImport, DataRepresentation, FlowCytometry, Proteomics, SingleCell, Software, SystemsBiology
Version 1.5.0
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
Linking To
Suggests knitr, rmarkdown
System Requirements
Enhances
URL https://github.com/cytolab/cytoMEM
See More
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report  

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package cytoMEM_1.5.0.tar.gz
Windows Binary cytoMEM_1.5.0.zip (64-bit only)
macOS Binary (x86_64) cytoMEM_1.5.0.tgz
macOS Binary (arm64) cytoMEM_1.5.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/cytoMEM
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/cytoMEM
Bioc Package Browser https://code.bioconductor.org/browse/cytoMEM/
Package Short Url https://bioconductor.org/packages/cytoMEM/
Package Downloads Report Download Stats