Publication Date:
2018-05-22
Description:
Interpretable dimensionality reduction of single cell transcriptome data with deep generative models Interpretable dimensionality reduction of single cell transcriptome data with deep generative models, Published online: 21 May 2018; doi:10.1038/s41467-018-04368-5 Although single-cell transcriptome data are increasingly available, their interpretation remains a challenge. Here, the authors present a dimensionality reduction approach that preserves both the local and global neighbourhood structures in the data thus enhancing its interpretability.
Electronic ISSN:
2041-1723
Topics:
Biology
,
Chemistry and Pharmacology
,
Natural Sciences in General
,
Physics
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