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Interpretable dimensionality reduction of single cell transcriptome data with deep generative models

Single-cell RNA-sequencing has great potential to discover cell types, identify cell states, trace development lineages, and reconstruct the spatial organization of cells. However, dimension reduction to interpret structure in single-cell sequencing data remains a challenge. Existing algorithms are...

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Detalhes bibliográficos
Publicado no:Nat Commun
Main Authors: Ding, Jiarui, Condon, Anne, Shah, Sohrab P.
Formato: Artigo
Idioma:Inglês
Publicado em: Nature Publishing Group UK 2018
Assuntos:
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC5962608/
https://ncbi.nlm.nih.gov/pubmed/29784946
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s41467-018-04368-5
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