Bioconductor - scAnnotatR

Bioconductor - scAnnotatR
Bioconductor 3.22
Software Packages
scAnnotatR
scAnnotatR
This is the
released
version of scAnnotatR; for the devel version, see
scAnnotatR
Pretrained learning models for cell type prediction on single cell RNA-sequencing data
DOI:
10.18129/B9.bioc.scAnnotatR
Bioconductor version:
Release (3.22)
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]
ORCID: 0000-0003-3436-3662
, Johannes Griss [cre]
ORCID: 0000-0003-2206-9511
Maintainer:
Johannes Griss
Citation (from within R, enter
citation("scAnnotatR")
):
Installation
To install this package, start R (version "4.5") 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")
1. Introduction to scAnnotatR
HTML
R Script
2. Training basic model
HTML
R Script
3. Training child model
HTML
R Script
Reference Manual
PDF
NEWS
Text
LICENSE
Text
Need some help? Ask on the Bioconductor Support site!
Details
biocViews
Classification
GeneExpression
SingleCell
Software
SupportVectorMachine
Transcriptomics
Version
1.16.1
In Bioconductor since
BioC 3.14 (R-4.1) (4.5 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
System Requirements
URL
Bug Reports
See More
Suggests
knitr
rmarkdown
scRNAseq
testthat
Linking To
Enhances
Depends On Me
Imports Me
Suggests Me
scAnnotatR.models
Links To Me
Build Report
Build Report
Package Archives
Follow
Installation
instructions to use this package in your R session.
Source Package
scAnnotatR_1.16.1.tar.gz
Windows Binary (x86_64)
scAnnotatR_1.16.1.zip
macOS Binary (x86_64)
scAnnotatR_1.16.1.tgz
macOS Binary (arm64)
scAnnotatR_1.16.1.tgz
Source Repository
git clone https://git.bioconductor.org/packages/scAnnotatR
Source Repository (Developer Access)
git clone git@git.bioconductor.org:packages/scAnnotatR
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