Learning interpretable cellular and gene signature embeddings from single-cell transcriptomic data
Learning interpretable cellular and gene signature embeddings from single-cell transcriptomic data
About this item
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Author / Creator
Zhao, Yifan , Cai, Huiyu , Zhang, Zuobai , Tang, Jian and Li, Yue
Publisher
London: Nature Publishing Group UK
Journal title
Language
English
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Publication information
Publisher
London: Nature Publishing Group UK
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Scope and Contents
Contents
The advent of single-cell RNA sequencing (scRNA-seq) technologies has revolutionized transcriptomic studies. However, large-scale integrative analysis of scRNA-seq data remains a challenge largely due to unwanted batch effects and the limited transferabilty, interpretability, and scalability of the existing computational methods. We present single-...
Alternative Titles
Full title
Learning interpretable cellular and gene signature embeddings from single-cell transcriptomic data
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TN_cdi_doaj_primary_oai_doaj_org_article_7990959eb2ba4fc09e678054e84e1c54
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_7990959eb2ba4fc09e678054e84e1c54
Other Identifiers
ISSN
2041-1723
E-ISSN
2041-1723
DOI
10.1038/s41467-021-25534-2
