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Benchmarking spatial and single-cell transcriptomics integration methods for transcript distribution prediction and cell type deconvolution.
Li, Bin; Zhang, Wen; Guo, Chuang; Xu, Hao; Li, Longfei; Fang, Minghao; Hu, Yinlei; Zhang, Xinye; Yao, Xinfeng; Tang, Meifang; Liu, Ke; Zhao, Xuetong; Lin, Jun; Cheng, Linzhao; Chen, Falai; Xue, Tian; Qu, Kun.
Affiliation
  • Li B; Department of Oncology, The First Affiliated Hospital of USTC, School of Basic Medical Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China.
  • Zhang W; Department of Oncology, The First Affiliated Hospital of USTC, School of Basic Medical Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China.
  • Guo C; Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China.
  • Xu H; Department of Oncology, The First Affiliated Hospital of USTC, School of Basic Medical Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China.
  • Li L; Department of Oncology, The First Affiliated Hospital of USTC, School of Basic Medical Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China.
  • Fang M; Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China.
  • Hu Y; Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China.
  • Zhang X; Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China.
  • Yao X; School of Mathematical Sciences, University of Science and Technology of China, Hefei, China.
  • Tang M; Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China.
  • Liu K; Department of Oncology, The First Affiliated Hospital of USTC, School of Basic Medical Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China.
  • Zhao X; Department of Oncology, The First Affiliated Hospital of USTC, School of Basic Medical Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China.
  • Lin J; Department of Oncology, The First Affiliated Hospital of USTC, School of Basic Medical Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China.
  • Cheng L; CAS Key Laboratory of Microbial Physiological and Metabolic Engineering, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China.
  • Chen F; Department of Oncology, The First Affiliated Hospital of USTC, School of Basic Medical Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China.
  • Xue T; Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China.
  • Qu K; Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China.
Nat Methods ; 19(6): 662-670, 2022 06.
Article in En | MEDLINE | ID: mdl-35577954
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Full text: 1 Database: MEDLINE Main subject: Benchmarking / Transcriptome Type of study: Prognostic_studies / Risk_factors_studies Language: En Journal: Nat Methods Journal subject: TECNICAS E PROCEDIMENTOS DE LABORATORIO Year: 2022 Type: Article Affiliation country: China
Fulltext
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Full text: 1 Database: MEDLINE Main subject: Benchmarking / Transcriptome Type of study: Prognostic_studies / Risk_factors_studies Language: En Journal: Nat Methods Journal subject: TECNICAS E PROCEDIMENTOS DE LABORATORIO Year: 2022 Type: Article Affiliation country: China