SCA: recovering single-cell heterogeneity through information-based dimensionality reduction
Abstract Dimensionality reduction summarizes the complex transcriptomic landscape of single-cell datasets for downstream analyses. Current approaches favor large cellular populations defined by many genes, at the expense of smaller and more subtly defined populations. Here, we present...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
BioMed Central
2023
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| Online Access: | https://hdl.handle.net/1721.1/152252 |