scAnnotatR

DOI: 10.18129/B9.bioc.scAnnotatR  

This package is for version 3.17 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: 3.17

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>

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

Installation

To install this package, start R (version "4.3") 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 1.6.0
In Bioconductor since BioC 3.14 (R-4.1) (2 years)
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_1.6.0.tar.gz
Windows Binary scAnnotatR_1.6.0.zip
macOS Binary (x86_64) scAnnotatR_1.6.0.tgz
macOS Binary (arm64) scAnnotatR_1.6.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/scAnnotatR
Source Repository (Developer Access) git clone [email protected]:packages/scAnnotatR
Bioc Package Browser https://code.bioconductor.org/browse/scAnnotatR/
Package Short Url https://bioconductor.org/packages/scAnnotatR/
Package Downloads Report Download Stats

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