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...

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Detalles Bibliográficos
Autores principales: Wang, Dongfang, Hou, Siyu, Zhang, Lei, Wang, Xiliang, Liu, Baolin, Zhang, Zemin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Method
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

Internet

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

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