iMAP: integration of multiple single-cell datasets by adversarial paired transfer networks
iMAP: integration of multiple single-cell datasets by adversarial paired transfer networks
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England: BioMed Central Ltd
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English
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England: BioMed Central Ltd
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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 generative adversarial networks. Compared with current...
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iMAP: integration of multiple single-cell datasets by adversarial paired transfer networks
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TN_cdi_doaj_primary_oai_doaj_org_article_fdc3dbc2c1b34562ae1d782a12ad93f9
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_fdc3dbc2c1b34562ae1d782a12ad93f9
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ISSN
1474-760X,1474-7596
E-ISSN
1474-760X
DOI
10.1186/s13059-021-02280-8
