Hierarchical progressive learning of cell identities in single-cell data
Classification methods for scRNA-seq data are limited in their ability to learn from multiple datasets simultaneously. Here the authors present scHPL, a hierarchical progressive learning method that automatically finds relationships between cell populations across multiple datasets and constructs a...
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| Autores principales: | , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Nature Portfolio
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/4e15acbcd00048f2abe98c564cc7ece7 |
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| Sumario: | Classification methods for scRNA-seq data are limited in their ability to learn from multiple datasets simultaneously. Here the authors present scHPL, a hierarchical progressive learning method that automatically finds relationships between cell populations across multiple datasets and constructs a classification tree. |
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