A Bayesian mixture model for clustering droplet-based single-cell transcriptomic data from population studies

A Bayesian mixture model for clustering droplet-based single-cell transcriptomic data from population studies

With the development of large scale single cell RNA-seq technology, population-scale scRNA-seq studies are emerging. Here, the authors develop BAMM-SC, a tool for clustering droplet-based scRNA-seq data from multiple individuals simultaneously.

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Detalles Bibliográficos
Autores principales: Zhe Sun, Li Chen, Hongyi Xin, Yale Jiang, Qianhui Huang, Anthony R. Cillo, Tracy Tabib, Jay K. Kolls, Tullia C. Bruno, Robert Lafyatis, Dario A. A. Vignali, Kong Chen, Ying Ding, Ming Hu, Wei Chen
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2019
Materias:
Science
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Acceso en línea:https://doaj.org/article/52d49e5908374e5ea58127ece365e62a
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https://doaj.org/article/52d49e5908374e5ea58127ece365e62a

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