haoharryfeng/NeuCA: NEUral network-based single-Cell Annotation tool

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.

Getting started

Package details

Bioconductor views Classification DataImport DataRepresentation GeneExpression NeuralNetwork Preprocessing RNASeq Sequencing SingleCell Software Transcription Transcriptomics
Maintainer
LicenseGPL-2
Version0.99.5
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("haoharryfeng/NeuCA")
haoharryfeng/NeuCA documentation built on Dec. 20, 2021, 2:48 p.m.