cytoMEM

DOI: 10.18129/B9.bioc.cytoMEM    

This package is for version 3.15 of Bioconductor; for the stable, up-to-date release version, see cytoMEM.

Marker Enrichment Modeling (MEM)

Bioconductor version: 3.15

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>

Installation

To install this package, start R (version "4.2") 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.

Documentation

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

browseVignettes("cytoMEM")

 

HTML	R Script	Intro_to_Marker_Enrichment_Modeling_Analysis
PDF		Reference Manual
Text		NEWS

Details

biocViews	CellBiology, Classification, Clustering, DataImport, DataRepresentation, FlowCytometry, Proteomics, SingleCell, Software, SystemsBiology
Version	1.0.0
In Bioconductor since	BioC 3.15 (R-4.2) (0.5 years)
License	GPL-3
Depends	R (>= 4.2.0)
Imports	gplots, tools, flowCore, grDevices, stats, utils, matrixStats, methods
LinkingTo
Suggests	knitr, rmarkdown
SystemRequirements
Enhances
URL	https://github.com/cytolab/cytoMEM
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_1.0.0.tar.gz
Windows Binary	cytoMEM_1.0.0.zip
macOS Binary (x86_64)	cytoMEM_1.0.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/cytoMEM
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/cytoMEM
Package Short Url	https://bioconductor.org/packages/cytoMEM/
Package Downloads Report	Download Stats