Generalizable and Scalable Visualization of Single-Cell Data Using Neural Networks
Visualization algorithms are fundamental tools for interpreting single-cell data. However, standard methods, such as t-stochastic neighbor embedding (t-SNE), are not scalable to datasets with millions of cells and the resulting visualizations cannot be generalized to analyze new datasets. Here we in...
| Main Authors: | , , |
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| Other Authors: | , |
| Format: | Article |
| Language: | English |
| Published: |
Cell Press,
2019-11-08T13:33:04Z.
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| Subjects: | |
| Online Access: | Get fulltext |