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A benchmark of batch-effect correction methods for single-cell RNA sequencing data
BACKGROUND: Large-scale single-cell transcriptomic datasets generated using different technologies contain batch-specific systematic variations that present a challenge to batch-effect removal and data integration. With continued growth expected in scRNA-seq data, achieving effective batch integrati...
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| Veröffentlicht in: | Genome Biol |
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| Hauptverfasser: | , , , , , , |
| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
BioMed Central
2020
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| Schlagworte: | |
| Online Zugang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6964114/ https://ncbi.nlm.nih.gov/pubmed/31948481 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s13059-019-1850-9 |
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