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scAnnotatR

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

Bioconductor version: 3.23 · Package version: 1.18.0

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.

Installation

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

BiocManager::install("scAnnotatR")

Details

MaintainerJohannes Griss <johannes.griss@meduniwien.ac.at>
AuthorVy Nguyen [aut] (ORCID: <https://orcid.org/0000-0003-3436-3662>), Johannes Griss [cre] (ORCID: <https://orcid.org/0000-0003-2206-9511>)
LicenseMIT + file LICENSE
URLhttps://github.com/grisslab/scAnnotatR
Bug Reportshttps://github.com/grisslab/scAnnotatR/issues/new
Downloads rank262
Source branchRELEASE_3_23
biocViewsClassification, GeneExpression, SingleCell, Software, SupportVectorMachine, Transcriptomics

Documentation

Download

Dependencies

Depends: R (>= 4.1), Seurat, SingleCellExperiment, SummarizedExperiment

Imports: dplyr, ggplot2, caret, ROCR, pROC, data.tree, methods, stats, e1071, ape, kernlab, AnnotationHub, utils

Suggests: knitr, rmarkdown, scRNAseq, testthat

Reverse dependencies

Suggests Me (1): scAnnotatR.models