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Enhancing droplet-based single-nucleus RNA-seq resolution using the semi-supervised machine learning classifier DIEM
Single-nucleus RNA sequencing (snRNA-seq) measures gene expression in individual nuclei instead of cells, allowing for unbiased cell type characterization in solid tissues. We observe that snRNA-seq is commonly subject to contamination by high amounts of ambient RNA, which can lead to biased downstr...
| Autores principales: | , , , , , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2020
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7335186/ https://www.ncbi.nlm.nih.gov/pubmed/32620816 http://dx.doi.org/10.1038/s41598-020-67513-5 |