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[Imputation method for dropout in single-cell transcriptome data].
Jiang, Chao; Hu, Longfei; Xu, Chunxiang; Ge, Qinyu; Zhao, Xiangwei.
Afiliação
  • Jiang C; State Key Laboratory of Bioelectronics, School of Biological Sciences and Medical Engineering, Southeast University, Nanjing 210096, P. R. China.
  • Hu L; School of Medicine & Holistic Integrative Medicine, Nanjing University of Chinese Medicine, Nanjing 210023, P. R. China.
  • Xu C; Singleron BiotechCo., Ltd, Nanjing 210018, P. R. China.
  • Ge Q; State Key Laboratory of Bioelectronics, School of Biological Sciences and Medical Engineering, Southeast University, Nanjing 210096, P. R. China.
  • Zhao X; State Key Laboratory of Bioelectronics, School of Biological Sciences and Medical Engineering, Southeast University, Nanjing 210096, P. R. China.
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi ; 40(4): 778-783, 2023 Aug 25.
Article em Zh | MEDLINE | ID: mdl-37666769
Single-cell transcriptome sequencing (scRNA-seq) can resolve the expression characteristics of cells in tissues with single-cell precision, enabling researchers to quantify cellular heterogeneity within populations with higher resolution, revealing potentially heterogeneous cell populations and the dynamics of complex tissues. However, the presence of a large number of technical zeros in scRNA-seq data will have an impact on downstream analysis of cell clustering, differential genes, cell annotation, and pseudotime, hindering the discovery of meaningful biological signals. The main idea to solve this problem is to make use of the potential correlation between cells and genes, and to impute the technical zeros through the observed data. Based on this, this paper reviewed the basic methods of imputing technical zeros in the scRNA-seq data and discussed the advantages and disadvantages of the existing methods. Finally, recommendations and perspectives on the use and development of the method were provided.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Transcriptoma Tipo de estudo: Prognostic_studies Idioma: Zh Revista: Sheng Wu Yi Xue Gong Cheng Xue Za Zhi Assunto da revista: ENGENHARIA BIOMEDICA Ano de publicação: 2023 Tipo de documento: Article País de publicação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Transcriptoma Tipo de estudo: Prognostic_studies Idioma: Zh Revista: Sheng Wu Yi Xue Gong Cheng Xue Za Zhi Assunto da revista: ENGENHARIA BIOMEDICA Ano de publicação: 2023 Tipo de documento: Article País de publicação: China