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Automatic identification of relevant genes from low-dimensional embeddings of single-cell RNA-seq data
MOTIVATION: Dimensionality reduction is a key step in the analysis of single-cell RNA-sequencing data. It produces a low-dimensional embedding for visualization and as a calculation base for downstream analysis. Nonlinear techniques are most suitable to handle the intrinsic complexity of large, hete...
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| Publicat a: | Bioinformatics |
|---|---|
| Autors principals: | , , , , |
| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
Oxford University Press
2020
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| Matèries: | |
| Accés en línia: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7520047/ https://ncbi.nlm.nih.gov/pubmed/32207520 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/bioinformatics/btaa198 |
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