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.

Bibliographic Details
Main Authors: 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
Format: Article
Language:English
Published: Nature Publishing Group 2019-04-01
Series:Nature Communications
Online Access:https://doi.org/10.1038/s41467-019-09639-3

Internet

https://doi.org/10.1038/s41467-019-09639-3

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