| Literature DB >> 35176143 |
Daoyu Duan1, Sijia He2, Emina Huang3, Ziyi Li4, Hao Feng1.
Abstract
SUMMARY: Correctly annotating individual cell's type is an important initial step in single cell RNA sequencing (scRNA-seq) data analysis. Here, we present NeuCA web server, a neural network-based scRNA-seq cell annotation tool with web-app portal and graphical user interface, for automatically assigning cell labels. NeuCA algorithm is accurate and exhaustive, maximizing the usage of measured cells for downstream analysis. NeuCA web server provides over 20 ready-to-use pre-trained classifiers for commonly used tissue types. As the first web-app tool with neural-network infrastructure implemented, NeuCA web will facilitate the research community in analyzing and annotating scRNA-seq data. AVAILABILITY: NeuCA web server is implemented with R Shiny application online at https://statbioinfo.shinyapps.io/NeuCA/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.Entities:
Year: 2022 PMID: 35176143 PMCID: PMC9004646 DOI: 10.1093/bioinformatics/btac108
Source DB: PubMed Journal: Bioinformatics ISSN: 1367-4803 Impact factor: 6.937