Statistical and machine learning methods for spatially resolved transcriptomics with histology.

Hu, Jian; Schroeder, Amelia; Coleman, Kyle; Chen, Chixiang; Auerbach, Benjamin J; Li, Mingyao

Hu, Jian; Schroeder, Amelia; Coleman, Kyle; Chen, Chixiang; Auerbach, Benjamin J; Li, Mingyao.

Afiliação

Hu J; Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA.
Schroeder A; Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA.
Coleman K; Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA.
Chen C; Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA.
Auerbach BJ; Graduate Group in Genomics and Computational Biology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA.
Li M; Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA.

Comput Struct Biotechnol J ; 19: 3829-3841, 2021.

Article em En | MEDLINE | ID: mdl-34285782

Palavras-chave

Cell-cell communications; Celltype deconvolution; Spatial clustering; Spatially resolved transcriptomics; Spatially variable genes

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Texto completo: 1 Base de dados: MEDLINE Idioma: En Revista: Comput Struct Biotechnol J Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Estados Unidos

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