Label-aware distance mitigates temporal and spatial variability for clustering and visualization of single-cell gene expression data
Abstract Clustering and visualization are essential parts of single-cell gene expression data analysis. The Euclidean distance used in most distance-based methods is not optimal. The batch effect, i.e., the variability among samples gathered from different times, tissues, and patients, introduces la...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2024-03-01
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| Series: | Communications Biology |
| Online Access: | https://doi.org/10.1038/s42003-024-05988-y |