scAnnotatR

DOI: 10.18129/B9.bioc.scAnnotatR    

This package is for version 3.15 of Bioconductor; for the stable, up-to-date release version, see scAnnotatR.

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

Bioconductor version: 3.15

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. scAnnotatR 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 "4.2") and enter:

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

BiocManager::install("scAnnotatR")

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("scAnnotatR")

 

HTML	R Script	1. Introduction to scAnnotatR
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 3.14 (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, AnnotationHub, utils
LinkingTo
Suggests	knitr, rmarkdown, scRNAseq, testthat
SystemRequirements
Enhances
URL	https://github.com/grisslab/scAnnotatR
BugReports	https://github.com/grisslab/scAnnotatR/issues/new
Depends On Me
Imports Me
Suggests Me	scAnnotatR.models
Links To Me
Build Report

Package Archives

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

Source Package	scAnnotatR_1.2.0.tar.gz
Windows Binary	scAnnotatR_1.2.0.zip
macOS Binary (x86_64)	scAnnotatR_1.2.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/scAnnotatR
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/scAnnotatR
Package Short Url	https://bioconductor.org/packages/scAnnotatR/
Package Downloads Report	Download Stats