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Data analysis guidelines for single-cell RNA-seq in biomedical studies and clinical applications.
Su, Min; Pan, Tao; Chen, Qiu-Zhen; Zhou, Wei-Wei; Gong, Yi; Xu, Gang; Yan, Huan-Yu; Li, Si; Shi, Qiao-Zhen; Zhang, Ya; He, Xiao; Jiang, Chun-Jie; Fan, Shi-Cai; Li, Xia; Cairns, Murray J; Wang, Xi; Li, Yong-Sheng.
  • Su M; State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, 211166, China.
  • Pan T; College of Biomedical Information and Engineering, the First Affiliated Hospital of Hainan Medical University, Hainan Medical University, Haikou, 571199, Hainan, China.
  • Chen QZ; State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, 211166, China.
  • Zhou WW; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, Heilongjiang, China.
  • Gong Y; State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, 211166, China.
  • Xu G; Department of Immunology, Nanjing Medical University, Nanjing, 211166, China.
  • Yan HY; College of Biomedical Information and Engineering, the First Affiliated Hospital of Hainan Medical University, Hainan Medical University, Haikou, 571199, Hainan, China.
  • Li S; State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, 211166, China.
  • Shi QZ; College of Biomedical Information and Engineering, the First Affiliated Hospital of Hainan Medical University, Hainan Medical University, Haikou, 571199, Hainan, China.
  • Zhang Y; State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, 211166, China.
  • He X; College of Biomedical Information and Engineering, the First Affiliated Hospital of Hainan Medical University, Hainan Medical University, Haikou, 571199, Hainan, China.
  • Jiang CJ; Department of Laboratory Medicine, Women and Children's Hospital of Chongqing Medical University, Chongqing, 401174, China.
  • Fan SC; Baylor College of Medicine, Houston, TX, 77030, USA.
  • Li X; Shenzhen Institute for Advanced Study, University of Electronic Science and Technology of China, Shenzhen, 518110, Guangdong, China.
  • Cairns MJ; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, Heilongjiang, China. lixia@hrbmu.edu.cn.
  • Wang X; School of Biomedical Sciences and Pharmacy, Faculty of Health and Medicine, the University of Newcastle, University Drive, Callaghan, NSW, 2308, Australia. murray.cairns@newcastle.edu.au.
  • Li YS; Precision Medicine Research Program, Hunter Medical Research Institute, New Lambton Heights, NSW, 2305, Australia. murray.cairns@newcastle.edu.au.
Mil Med Res ; 9(1): 68, 2022 12 02.
Article in English | MEDLINE | ID: covidwho-2196508
ABSTRACT
The application of single-cell RNA sequencing (scRNA-seq) in biomedical research has advanced our understanding of the pathogenesis of disease and provided valuable insights into new diagnostic and therapeutic strategies. With the expansion of capacity for high-throughput scRNA-seq, including clinical samples, the analysis of these huge volumes of data has become a daunting prospect for researchers entering this field. Here, we review the workflow for typical scRNA-seq data analysis, covering raw data processing and quality control, basic data analysis applicable for almost all scRNA-seq data sets, and advanced data analysis that should be tailored to specific scientific questions. While summarizing the current methods for each analysis step, we also provide an online repository of software and wrapped-up scripts to support the implementation. Recommendations and caveats are pointed out for some specific analysis tasks and approaches. We hope this resource will be helpful to researchers engaging with scRNA-seq, in particular for emerging clinical applications.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Biomedical Research / Data Analysis Type of study: Prognostic study Limits: Humans Language: English Journal: Mil Med Res Year: 2022 Document Type: Article Affiliation country: S40779-022-00434-8

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Biomedical Research / Data Analysis Type of study: Prognostic study Limits: Humans Language: English Journal: Mil Med Res Year: 2022 Document Type: Article Affiliation country: S40779-022-00434-8