Hierarchical cell-type identifier accurately distinguishes immune-cell subtypes enabling precise profiling of tissue microenvironment with single-cell RNA-sequencing

Author:

Lee Joongho1,Kim Minsoo1,Kang Keunsoo2,Yang Chul-Su3,Yoon Seokhyun4ORCID

Affiliation:

1. Dept. of Computer Science, College of SW Convergence, Dankook University , Yongin-si, Korea, 16890

2. Dept. of Microbiology, College of Natural Sciences, Dankook University , Cheonan-si, Korea, 31116

3. Dept. of Molecular and Life Science, Center for Bionano Intelligence Education and Research, Hanyang University , Ansan, Korea, 15588

4. Dept. of Electronics & Electrical Eng., College of Engineering, Dankook University , Yongin-si Korea, 16890

Abstract

AbstractSingle-cell RNA-seq enabled in-depth study on tissue micro-environment and immune-profiling, where a crucial step is to annotate cell identity. Immune cells play key roles in many diseases, whereas their activities are hard to track due to their diverse and highly variable nature. Existing cell-type identifiers had limited performance for this purpose. We present HiCAT, a hierarchical, marker-based cell-type identifier utilising gene set analysis for statistical scoring for given markers. It features successive identification of major-type, minor-type and subsets utilising subset markers structured in a three-level taxonomy tree. Comparison with manual annotation and pairwise match test showed HiCAT outperforms others in major- and minor-type identification. For subsets, we qualitatively evaluated the marker expression profile demonstrating that HiCAT provide the clearest immune-cell landscape. HiCAT was also used for immune-cell profiling in ulcerative colitis and discovered distinct features of the disease in macrophage and T-cell subsets that could not be identified previously.

Funder

Ministry of Education, Science and Technology

Publisher

Oxford University Press (OUP)

Subject

Molecular Biology,Information Systems

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