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Scalable preprocessing for sparse scRNA-seq data exploiting prior knowledge
MOTIVATION: Single cell RNA-seq (scRNA-seq) data contains a wealth of information which has to be inferred computationally from the observed sequencing reads. As the ability to sequence more cells improves rapidly, existing computational tools suffer from three problems. (i) The decreased reads-per-...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Oxford University Press
2018
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6022691/ https://www.ncbi.nlm.nih.gov/pubmed/29949988 http://dx.doi.org/10.1093/bioinformatics/bty293 |