EpiScanpy: integrated single-cell epigenomic analysis
The authors present epiScanpy: a computational framework for the analysis of single-cell epigenomic data, both ATAC-seq and DNA methylation data, with examples for clustering, cell type identification, trajectory learning and atlas integration - and show its performance in distinguishing cell types.
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| Autores principales: | , , , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Nature Portfolio
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/080e8714432f46029536734062f84ff2 |
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| Sumario: | The authors present epiScanpy: a computational framework for the analysis of single-cell epigenomic data, both ATAC-seq and DNA methylation data, with examples for clustering, cell type identification, trajectory learning and atlas integration - and show its performance in distinguishing cell types. |
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