Interpretable dimensionality reduction of single cell transcriptome data with deep generative models
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.
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Autores principales: | Jiarui Ding, Anne Condon, Sohrab P. Shah |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2018
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Materias: | |
Acceso en línea: | https://doaj.org/article/374e2f7ee4b743cebc2a0022380ea83b |
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