NeuCA web server: a neural network-based cell annotation tool with web-app and GUI
Daoyu Duan1, Sijia He2, Emina Huang3
1Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH 44106, USA.
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 And Implementation:
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.
