Automated annotation of rare-cell types from single-cell RNA-sequencing data through synthetic oversampling

被引:0
|
作者
Saptarshi Bej
Anne-Marie Galow
Robert David
Markus Wolfien
Olaf Wolkenhauer
机构
[1] University of Rostock,Department of Systems Biology and Bioinformatics
[2] Technical University of Munich,Leibniz
[3] Research Institute for Farm Animal Biology,Institute for Food Systems Biology
[4] Rostock University Medical Centre,Institute of Genome Biology
[5] University of Rostock,Department of Cardiac Surgery
[6] Stellenbosch University,Department of Life, Light and Matter
来源
关键词
Single-cell RNA-sequencing; Imbalanced datasets; Rare cell type detection; LoRAS algorithm; Automated cell annotation;
D O I
暂无
中图分类号
学科分类号
摘要
引用
收藏
相关论文
共 50 条
  • [1] Automated annotation of rare-cell types from single-cell RNA-sequencing data through synthetic oversampling
    Bej, Saptarshi
    Galow, Anne-Marie
    David, Robert
    Wolfien, Markus
    Wolkenhauer, Olaf
    BMC BIOINFORMATICS, 2021, 22 (01)
  • [2] scAnnotate: an automated cell-type annotation tool for single-cell RNA-sequencing data
    Ji, Xiangling
    Tsao, Danielle
    Bai, Kailun
    Tsao, Min
    Xing, Li
    Zhang, Xuekui
    BIOINFORMATICS ADVANCES, 2023, 3 (01):
  • [3] scCATCH: Automatic Annotation on Cell Types of Clusters from Single-Cell RNA Sequencing Data
    Shao, Xin
    Liao, Jie
    Lu, Xiaoyan
    Xue, Rui
    Ai, Ni
    Fan, Xiaohui
    ISCIENCE, 2020, 23 (03)
  • [4] Sub-Cluster Identification through Semi-Supervised Optimization of Rare-Cell Silhouettes (SCISSORS) in single-cell RNA-sequencing
    Leary, Jack R.
    Xu, Yi
    Morrison, Ashley B.
    Jin, Chong
    Shen, Emily C.
    Kuhlers, Peyton C.
    Su, Ye
    Rashid, Naim U.
    Yeh, Jen Jen
    Peng, Xianlu Laura
    BIOINFORMATICS, 2023, 39 (08)
  • [5] Multi-Target Integration and Annotation of Single-Cell RNA-Sequencing Data
    Bhandari, Sapan
    Whitener, Nathan P.
    Zhao, Konghao
    Khuri, Natalia
    13TH ACM INTERNATIONAL CONFERENCE ON BIOINFORMATICS, COMPUTATIONAL BIOLOGY AND HEALTH INFORMATICS, BCB 2022, 2022,
  • [6] scAnnotatR: framework to accurately classify cell types in single-cell RNA-sequencing data
    Vy Nguyen
    Johannes Griss
    BMC Bioinformatics, 23
  • [7] scAnnotatR: framework to accurately classify cell types in single-cell RNA-sequencing data
    Nguyen, Vy
    Griss, Johannes
    BMC BIOINFORMATICS, 2022, 23 (01)
  • [8] Benchmarking clustering algorithms on estimating the number of cell types from single-cell RNA-sequencing data
    Lijia Yu
    Yue Cao
    Jean Y. H. Yang
    Pengyi Yang
    Genome Biology, 23
  • [9] Benchmarking clustering algorithms on estimating the number of cell types from single-cell RNA-sequencing data
    Yu, Lijia
    Cao, Yue
    Yang, Jean Y. H.
    Yang, Pengyi
    GENOME BIOLOGY, 2022, 23 (01)
  • [10] scQCEA: a framework for annotation and quality control report of single-cell RNA-sequencing data
    Nassiri, Isar
    Fairfax, Benjamin
    Lee, Angela
    Wu, Yanxia
    Buck, David
    Piazza, Paolo
    BMC GENOMICS, 2023, 24 (01)