Generalized and scalable trajectory inference in single-cell omics data with VIA

Scalable trajectory inference for multi-omic single cell datasets is challenging in terms of capturing non-tree complex topologies. Here the authors present a method, VIA, that scales to millions of cells across multiple omic modalities using lazy-teleporting random walks.

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Autores principales: Shobana V. Stassen, Gwinky G. K. Yip, Kenneth K. Y. Wong, Joshua W. K. Ho, Kevin K. Tsia
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
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Acceso en línea:https://doaj.org/article/9bd006f35d39495d922c8c86b7b6b9a2
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