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...

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Detalles Bibliográficos
Autores principales: Alvarez, Marcus, Rahmani, Elior, Jew, Brandon, Garske, Kristina M., Miao, Zong, Benhammou, Jihane N., Ye, Chun Jimmie, Pisegna, Joseph R., Pietiläinen, Kirsi H., Halperin, Eran, Pajukanta, Päivi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Article
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

Internet

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

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