Cargando…
Assessing Single-Cell Transcriptomic Variability through Density-Preserving Data Visualization
Nonlinear data-visualization methods, such as t-SNE and UMAP, summarize the complex transcriptomic landscape of single cells in 2D or 3D, but they neglect the local density of data points in the original space, often resulting in misleading visualizations where densely populated subsets of cells are...
| Autores principales: | , , |
|---|---|
| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
2021
|
| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8195812/ https://www.ncbi.nlm.nih.gov/pubmed/33462509 http://dx.doi.org/10.1038/s41587-020-00801-7 |