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NeuCA

NEUral network-based single-Cell Annotation tool


Bioconductor version: Release (3.18)

NeuCA is is a neural-network based method for scRNA-seq data annotation. It can automatically adjust its classification strategy depending on cell type correlations, to accurately annotate cell. NeuCA can automatically utilize the structure information of the cell types through a hierarchical tree to improve the annotation accuracy. It is especially helpful when the data contain closely correlated cell types.

Author: Ziyi Li [aut], Hao Feng [aut, cre]

Maintainer: Hao Feng <hxf155 at case.edu>

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

Installation

To install this package, start R (version "4.3") and enter:


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

BiocManager::install("NeuCA")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

Reference Manual PDF

Details

biocViews Classification, DataImport, DataRepresentation, GeneExpression, NeuralNetwork, Preprocessing, RNASeq, Sequencing, SingleCell, Software, Transcription, Transcriptomics
Version 1.8.0
In Bioconductor since BioC 3.14 (R-4.1) (2.5 years)
License GPL-2
Depends R (>= 3.5.0), keras, limma, e1071, SingleCellExperiment
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Suggests BiocStyle, knitr, rmarkdown, networkD3
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Package Archives

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

Source Package
Windows Binary NeuCA_1.8.0.zip
macOS Binary (x86_64) NeuCA_1.8.0.tgz
macOS Binary (arm64)
Source Repository git clone https://git.bioconductor.org/packages/NeuCA
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/NeuCA
Bioc Package Browser https://code.bioconductor.org/browse/NeuCA/
Package Short Url https://bioconductor.org/packages/NeuCA/
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