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CellScore

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

Tool for Evaluation of Cell Identity from Transcription Profiles


Bioconductor version: Development (3.19)

The CellScore package contains functions to evaluate the cell identity of a test sample, given a cell transition defined with a starting (donor) cell type and a desired target cell type. The evaluation is based upon a scoring system, which uses a set of standard samples of known cell types, as the reference set. The functions have been carried out on a large set of microarray data from one platform (Affymetrix Human Genome U133 Plus 2.0). In principle, the method could be applied to any expression dataset, provided that there are a sufficient number of standard samples and that the data are normalized.

Author: Nancy Mah [aut, cre], Katerina Taskova [aut], Justin Marsh [aut]

Maintainer: Nancy Mah <nancy.l.mah at googlemail.com>

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

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("CellScore")

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("CellScore")
R packages: CellScore PDF R Script
Reference Manual PDF

Details

biocViews DataImport, GeneExpression, Microarray, MultipleComparison, ReportWriting, Software, Transcription, Visualization
Version 1.23.0
In Bioconductor since BioC 3.7 (R-3.5) (6 years)
License GPL-3
Depends R (>= 4.3.0)
Imports Biobase(>= 2.39.1), graphics (>= 3.5.0), grDevices (>= 3.5.0), gplots (>= 3.0.1), lsa (>= 0.73.1), methods (>= 3.5.0), RColorBrewer (>= 1.1-2), squash (>= 1.0.8), stats (>= 3.5.0), utils (>= 3.5.0), SummarizedExperiment
System Requirements
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Suggests hgu133plus2CellScore, knitr, testthat (>= 3.0.0)
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Package Archives

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

Source Package CellScore_1.23.0.tar.gz
Windows Binary CellScore_1.23.0.zip
macOS Binary (x86_64) CellScore_1.23.0.tgz
macOS Binary (arm64)
Source Repository git clone https://git.bioconductor.org/packages/CellScore
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/CellScore
Bioc Package Browser https://code.bioconductor.org/browse/CellScore/
Package Short Url https://bioconductor.org/packages/CellScore/
Package Downloads Report Download Stats