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Accurate integration of multiple heterogeneous single-cell RNA-seq data sets by learning contrastive biological variation
For most biological and medical applications of single-cell transcriptomics, an integrative study of multiple heterogeneous single-cell RNA sequencing (scRNA-seq) data sets is crucial. However, present approaches are unable to integrate diverse data sets from various biological conditions effectivel...
| Autores principales: | , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Cold Spring Harbor Laboratory Press
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10317120/ https://www.ncbi.nlm.nih.gov/pubmed/37308294 http://dx.doi.org/10.1101/gr.277522.122 |