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iMAP: integration of multiple single-cell datasets by adversarial paired transfer networks
The integration of single-cell RNA-sequencing datasets from multiple sources is critical for deciphering cell-to-cell heterogeneities and interactions in complex biological systems. We present a novel unsupervised batch effect removal framework, called iMAP, based on both deep autoencoders and gener...
| Autores principales: | , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7891139/ https://www.ncbi.nlm.nih.gov/pubmed/33602306 http://dx.doi.org/10.1186/s13059-021-02280-8 |