Benchmarking spatial and single-cell transcriptomics integration methods for transcript distribution...
Benchmarking spatial and single-cell transcriptomics integration methods for transcript distribution prediction and cell type deconvolution
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Author / Creator
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 and Qu, Kun
Publisher
New York: Nature Publishing Group US
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Language
English
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Publisher
New York: Nature Publishing Group US
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Contents
Spatial transcriptomics approaches have substantially advanced our capacity to detect the spatial distribution of RNA transcripts in tissues, yet it remains challenging to characterize whole-transcriptome-level data for single cells in space. Addressing this need, researchers have developed integration methods to combine spatial transcriptomic data...
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Full title
Benchmarking spatial and single-cell transcriptomics integration methods for transcript distribution prediction and cell type deconvolution
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Record Identifier
TN_cdi_proquest_miscellaneous_2665559942
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_miscellaneous_2665559942
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ISSN
1548-7091
E-ISSN
1548-7105
DOI
10.1038/s41592-022-01480-9
