Abstract
The advent of droplet-based transcriptomics platforms has enabled parallel screening over thousands or millions of cells. One of the challenging issues is to identify the rare cells from the ultra-large scRNA-seq data. Existing algorithms to find rare cells are time consuming or memory-exhausting. We propose an efficient and accurate method, Discovery of Rare Cells (DoRC). The rareness scores generated by DoRC can help biologists focus the downstream analyses only on a fraction of expression profiles within ultra-large scRNA-seq data. We also demonstrate the efficacy of DoRC in delineating human blood dendritic cell sub-types using ∼68k single-cell expression profiles of human blood cells. DoRC can recover artificially planted rare cells and is sensitive to cell type identities as well.
Original language | English |
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Title of host publication | Proceedings - 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019 |
Editors | Illhoi Yoo, Jinbo Bi, Xiaohua Tony Hu |
Pages | 111-116 |
Number of pages | 6 |
ISBN (Electronic) | 9781728118673 |
DOIs | |
State | Published - Nov 2019 |
Event | 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019 - San Diego, United States Duration: Nov 18 2019 → Nov 21 2019 |
Publication series
Name | Proceedings - 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019 |
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Conference
Conference | 2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019 |
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Country/Territory | United States |
City | San Diego |
Period | 11/18/19 → 11/21/19 |
Bibliographical note
Funding Information:We would like to thank Dr Aashi Jindal for fruitful discussions. This work is supported in part by the National Natural Science Foundation of China under Grants (No.61622213, No.61732009), the 111 Project (No.B18059) and the Hunan Provincial Science and Technology Program (2018WK4001).
Publisher Copyright:
© 2019 IEEE.
Keywords
- anomaly detection
- isolation forest
- rare cells
- scRNA-seq
- transcriptomics
ASJC Scopus subject areas
- Biochemistry
- Biotechnology
- Molecular Medicine
- Modeling and Simulation
- Health Informatics
- Pharmacology (medical)
- Public Health, Environmental and Occupational Health