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Optimal Transport improves cell-cell similarity inference in single-cell omics data

Geert-Jan Huizing, View ORCID ProfileGabriel Peyré, View ORCID ProfileLaura Cantini
doi: https://doi.org/10.1101/2021.03.19.436159
Geert-Jan Huizing
1Computational Systems Biology Team, Institut de Biologie de l’Ecole Normale Supérieure, CNRS, INSERM, Ecole Normale Supérieure, Université PSL, 75005 Paris, France
2Département de mathématiques et applications de l’Ecole Normale Supérieure, CNRS, Ecole Normale Supérieure, Université PSL, 75005, Paris, France
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  • For correspondence: laura.cantini@ens.fr huizing@ens.fr
Gabriel Peyré
2Département de mathématiques et applications de l’Ecole Normale Supérieure, CNRS, Ecole Normale Supérieure, Université PSL, 75005, Paris, France
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Laura Cantini
1Computational Systems Biology Team, Institut de Biologie de l’Ecole Normale Supérieure, CNRS, INSERM, Ecole Normale Supérieure, Université PSL, 75005 Paris, France
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  • For correspondence: laura.cantini@ens.fr huizing@ens.fr
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Posted March 20, 2021.
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Optimal Transport improves cell-cell similarity inference in single-cell omics data
Geert-Jan Huizing, Gabriel Peyré, Laura Cantini
bioRxiv 2021.03.19.436159; doi: https://doi.org/10.1101/2021.03.19.436159
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Optimal Transport improves cell-cell similarity inference in single-cell omics data
Geert-Jan Huizing, Gabriel Peyré, Laura Cantini
bioRxiv 2021.03.19.436159; doi: https://doi.org/10.1101/2021.03.19.436159

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