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Batch alignment of single-cell transcriptomics data using deep metric learning
- Source :
- Nature Communications, Vol 14, Iss 1, Pp 1-15 (2023)
- Publication Year :
- 2023
- Publisher :
- Nature Portfolio, 2023.
-
Abstract
- 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.
- Subjects :
- Science
Subjects
Details
- Language :
- English
- ISSN :
- 20411723
- Volume :
- 14
- Issue :
- 1
- Database :
- Directory of Open Access Journals
- Journal :
- Nature Communications
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.55c558e1aa9048d0a0a058fc0983bef1
- Document Type :
- article
- Full Text :
- https://doi.org/10.1038/s41467-023-36635-5