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Batch-Corrected Distance Mitigates Temporal and Spatial Variability for Clustering and Visualization of Single-Cell Gene Expression Data
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. Batch effect, i.e., the variability among samples gathered from different times, tissues, and patients, introduces large between-g...
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| Publicado no: | bioRxiv |
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| Main Authors: | , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Cold Spring Harbor Laboratory
2020
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7553164/ https://ncbi.nlm.nih.gov/pubmed/33052339 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1101/2020.10.08.332080 |
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