scClassifR

DOI: 10.18129/B9.bioc.scClassifR    

This package is deprecated. It will probably be removed from Bioconductor. Please refer to the package end-of-life guidelines for more information.

This package is for version 3.14 of Bioconductor. This package has been removed from Bioconductor. For the last stable, up-to-date release version, see scClassifR.

Pretrained learning models for cell type prediction on single cell RNA-sequencing data

Bioconductor version: 3.14

The package comprises a set of pretrained machine learning models to predict basic immune cell types. This enables all users to quickly get a first annotation of the cell types present in their dataset without requiring prior knowledge. scClassifR also allows users to train their own models to predict new cell types based on specific research needs.

Author: Vy Nguyen [aut] , Johannes Griss [cre]

Maintainer: Johannes Griss <johannes.griss at meduniwien.ac.at>

Installation

To install this package, start R (version "4.1") and enter:

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

BiocManager::install("scClassifR")

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("scClassifR")

 

HTML	R Script	1. Introduction to scClassifR
HTML	R Script	2. Training basic model
HTML	R Script	3. Training child model
PDF		Reference Manual
Text		NEWS
Text		LICENSE

Details

biocViews	Classification, GeneExpression, SingleCell, Software, SupportVectorMachine, Transcriptomics
Version	1.2.0
In Bioconductor since	BioC 3.13 (R-4.1) (1 year)
License	MIT + file LICENSE
Depends	R (>= 4.1), Seurat, SingleCellExperiment, SummarizedExperiment
Imports	dplyr, ggplot2, caret, ROCR, pROC, data.tree, methods, stats, e1071, ape, kernlab, utils
LinkingTo
Suggests	knitr, rmarkdown, scRNAseq, testthat
SystemRequirements
Enhances
URL
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report

Package Archives

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

Source Package	scClassifR_1.2.0.tar.gz
Windows Binary	scClassifR_1.2.0.zip
macOS 10.13 (High Sierra)	scClassifR_1.2.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/scClassifR
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/scClassifR
Package Short Url	https://bioconductor.org/packages/scClassifR/
Package Downloads Report	Download Stats