Batch alignment of single-cell transcriptomics data using deep metric learning
The increasing scale of single-cell RNA-seq studies presents new challenge for integrating datasets from different batches. Here, the authors develop scDML, a tool that simultaneously removes batch effects, improves clustering performance, recovers true cell types, and scales well to large datasets.
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2023-02-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-023-36635-5 |