cytoMEM
This package is for version 3.18 of Bioconductor; for the stable, up-to-date release version, see cytoMEM.
Marker Enrichment Modeling (MEM)
Bioconductor version: 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("cytoMEM")):
Installation
To install this package, start R (version "4.3") 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")| 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 | 1.6.0 |
| In Bioconductor since | BioC 3.15 (R-4.2) (2 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_1.6.0.tar.gz |
| Windows Binary | cytoMEM_1.6.0.zip |
| macOS Binary (x86_64) | cytoMEM_1.6.0.tgz |
| macOS Binary (arm64) | cytoMEM_1.6.0.tgz |
| Source Repository | git clone https://git.bioconductor.org/packages/cytoMEM |
| Source Repository (Developer Access) | git clone [email protected]:packages/cytoMEM |
| Bioc Package Browser | https://code.bioconductor.org/browse/cytoMEM/ |
| Package Short Url | https://bioconductor.org/packages/cytoMEM/ |
| Package Downloads Report | Download Stats |