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scClassify

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

scClassify: single-cell Hierarchical Classification


Bioconductor version: Development (3.19)

scClassify is a multiscale classification framework for single-cell RNA-seq data based on ensemble learning and cell type hierarchies, enabling sample size estimation required for accurate cell type classification and joint classification of cells using multiple references.

Author: Yingxin Lin

Maintainer: Yingxin Lin <yingxin.lin at sydney.edu.au>

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

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("scClassify")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

Reference Manual PDF

Details

biocViews Classification, GeneExpression, SingleCell, Software
Version 1.15.0
In Bioconductor since BioC 3.11 (R-4.0) (4 years)
License GPL-3
Depends R (>= 4.0)
Imports S4Vectors, limma, ggraph, igraph, methods, cluster, minpack.lm, mixtools, BiocParallel, proxy, proxyC, Matrix, ggplot2, hopach, diptest, mgcv, stats, graphics, statmod, Cepo
System Requirements
URL
Bug Reports https://github.com/SydneyBioX/scClassify/issues
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Suggests knitr, rmarkdown, BiocStyle, pkgdown
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Package Archives

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

Source Package
Windows Binary
macOS Binary (x86_64)
macOS Binary (arm64)
Source Repository git clone https://git.bioconductor.org/packages/scClassify
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/scClassify
Package Short Url https://bioconductor.org/packages/scClassify/
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