scmap

A tool for unsupervised projection of single cell RNA-seq data


Bioconductor version: Release (3.19)

Single-cell RNA-seq (scRNA-seq) is widely used to investigate the composition of complex tissues since the technology allows researchers to define cell-types using unsupervised clustering of the transcriptome. However, due to differences in experimental methods and computational analyses, it is often challenging to directly compare the cells identified in two different experiments. scmap is a method for projecting cells from a scRNA-seq experiment on to the cell-types or individual cells identified in a different experiment.

Author: Vladimir Kiselev

Maintainer: Vladimir Kiselev <vladimir.yu.kiselev at gmail.com>

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

Installation

To install this package, start R (version "4.4") and enter:


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

BiocManager::install("scmap")

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("scmap")
`scmap` package vignette HTML R Script
Reference Manual PDF
NEWS Text
LICENSE Text

Details

biocViews Classification, DataImport, DataRepresentation, GeneExpression, ImmunoOncology, Preprocessing, RNASeq, Sequencing, SingleCell, Software, SupportVectorMachine, Transcription, Transcriptomics, Visualization
Version 1.26.0
In Bioconductor since BioC 3.6 (R-3.4) (7 years)
License GPL-3
Depends R (>= 3.4)
Imports Biobase, SingleCellExperiment, SummarizedExperiment, BiocGenerics, S4Vectors, dplyr, reshape2, matrixStats, proxy, utils, googleVis, ggplot2, methods, stats, e1071, randomForest, Rcpp (>= 0.12.12)
System Requirements
URL https://github.com/hemberg-lab/scmap
Bug Reports https://support.bioconductor.org/t/scmap/
See More
Suggests knitr, rmarkdown, BiocStyle
Linking To Rcpp, RcppArmadillo
Enhances
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Package Archives

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

Source Package scmap_1.26.0.tar.gz
Windows Binary scmap_1.26.0.zip
macOS Binary (x86_64) scmap_1.26.0.tgz
macOS Binary (arm64) scmap_1.26.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/scmap
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/scmap
Bioc Package Browser https://code.bioconductor.org/browse/scmap/
Package Short Url https://bioconductor.org/packages/scmap/
Package Downloads Report Download Stats