cytoMEM
This is the development version of cytoMEM; for the stable release version, see cytoMEM.
Marker Enrichment Modeling (MEM)
Bioconductor version: Development (3.20)
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("cytoMEM")
):
Installation
To install this package, start R (version "4.4") 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 | ||
NEWS | Text |
Details
biocViews | CellBiology, Classification, Clustering, DataImport, DataRepresentation, FlowCytometry, Proteomics, SingleCell, Software, SystemsBiology |
Version | 1.9.0 |
In Bioconductor since | BioC 3.15 (R-4.2) (2.5 years) |
License | GPL-3 |
Depends | R (>= 4.2.0) |
Imports | gplots, tools, flowCore, grDevices, stats, utils, matrixStats, methods |
System Requirements | |
URL | https://github.com/cytolab/cytoMEM |
See More
Suggests | knitr, rmarkdown |
Linking To | |
Enhances | |
Depends On Me | |
Imports Me | |
Suggests Me | |
Links To Me | |
Build Report | Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
Source Package | cytoMEM_1.9.0.tar.gz |
Windows Binary | cytoMEM_1.9.0.zip |
macOS Binary (x86_64) | cytoMEM_1.9.0.tgz |
macOS Binary (arm64) | cytoMEM_1.9.0.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 |