NeuCA web server: a neural network-based cell annotation tool with web-app and GUI

Daoyu Duan, Sijia He, Emina Huang, Ziyi Li, Hao Feng

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish (US)
Pages (from-to)2361-2363
Number of pages3
JournalBioinformatics
Volume38
Issue number8
DOIs
StatePublished - Apr 15 2022

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

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