Fast and precise single-cell data analysis using a hierarchical autoencoder
Accurate analysis of single-cell RNA sequencing (scRNA-seq) data is affected by issues including technical noise and high dropout rate. Here, the authors develop a hierarchical autoencoder, scDHA, which outperforms existing methods in scRNA-seq analyses such as cell segregation and classification.
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Publishing Group
2021-02-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-021-21312-2 |