This package is for version 3.14 of Bioconductor; for the stable, up-to-date release version, see scmap.
Bioconductor version: 3.14
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")
):
To install this package, start R (version "4.1") 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.
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("scmap")
HTML | R Script | `scmap` package vignette |
Reference Manual | ||
Text | NEWS | |
Text | LICENSE |
biocViews | Classification, DataImport, DataRepresentation, GeneExpression, ImmunoOncology, Preprocessing, RNASeq, Sequencing, SingleCell, Software, SupportVectorMachine, Transcription, Transcriptomics, Visualization |
Version | 1.16.0 |
In Bioconductor since | BioC 3.6 (R-3.4) (4.5 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) |
LinkingTo | Rcpp, RcppArmadillo |
Suggests | knitr, rmarkdown |
SystemRequirements | |
Enhances | |
URL | https://github.com/hemberg-lab/scmap |
BugReports | https://support.bioconductor.org/t/scmap/ |
Depends On Me | |
Imports Me | |
Suggests Me | |
Links To Me | |
Build Report |
Follow Installation instructions to use this package in your R session.
Source Package | scmap_1.16.0.tar.gz |
Windows Binary | scmap_1.16.0.zip (32- & 64-bit) |
macOS 10.13 (High Sierra) | scmap_1.16.0.tgz |
Source Repository | git clone https://git.bioconductor.org/packages/scmap |
Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/scmap |
Package Short Url | https://bioconductor.org/packages/scmap/ |
Package Downloads Report | Download Stats |
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