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Probabilistic tensor decomposition extracts better latent embeddings from single-cell multiomic data
Single-cell sequencing technology enables the simultaneous capture of multiomic data from multiple cells. The captured data can be represented by tensors, i.e. the higher-rank matrices. However, the existing analysis tools often take the data as a collection of two-order matrices, renouncing the cor...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Oxford University Press
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10450184/ https://www.ncbi.nlm.nih.gov/pubmed/37403780 http://dx.doi.org/10.1093/nar/gkad570 |