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Matrix factorization and transfer learning uncover regulatory biology across multiple single-cell ATAC-seq data sets
While the methods available for single-cell ATAC-seq analysis are well optimized for clustering cell types, the question of how to integrate multiple scATAC-seq data sets and/or sequencing modalities is still open. We present an analysis framework that enables such integration across scATAC-seq data...
| Autores principales: | , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Oxford University Press
2020
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7337516/ https://www.ncbi.nlm.nih.gov/pubmed/32392348 http://dx.doi.org/10.1093/nar/gkaa349 |