deCS deCS: A tool for systematic cell type annotations of single-cell RNA sequencing data among human tissues

Introduction

Single-cell RNA sequencing (scRNA-seq) is rapidly accelerate our understanding of the cellular compositions of complex tissues. Yet, one major limitation for current protocols rely on manual annotations, which are subjectivity and time-consuming. The increasing numbers of scRNA-seq data sets, as well as numerous genetic studies, enable us to build a comprehensive cell type reference atlas. Here, we present deCS, for automatic cell type annotations based on a comprehensive collection of human cell type expression profiles or list of marker genes. We applied deCS to single-cell data sets from various tissues, and systematically evaluated the annotation accuracy under different conditions. Under the same conditions, deCS runs faster and have comparable even better accuracy than the competitive tools.

Publications

  1. deCS: A tool for systematic cell type annotations of single-cell RNA sequencing data among human tissues
    Cite this
    Guangsheng Pei, Fangfang Yan, Lukas M. Simon, Yulin Dai, Peilin Jia, Zhongming Zhao, -
    Cited by 1 (Google Schoolar as of December 13, 2021)

Credits

  1. Guangsheng Pei peiguangsheng@gmail.com
    Investigator

    School of Biomedical Informatics, The University of Texas Health Science Center at Houston, United States of America

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Summary
AccessionBT007286
Tool TypeApplication
CategoryscRNA-seq analysis
PlatformsLinux/Unix, Windows
TechnologiesR
User InterfaceTerminal Command Line
Download Count0
Country/RegionUnited States of America
Submitted ByGuangsheng Pei
Fundings

National Institutes of Health grants (R01LM012806, R01DE030122, and R01DE029818). Cancer Prevention and Research Institute of Texas (CPRIT RP180734 and RP210045).