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A fast and efficient count-based matrix factorization method for detecting cell types from single-cell RNAseq data.

Shiquan SunYabo ChenYang LiuXuequn Shang
Published in: BMC systems biology (2019)
In this paper, we proposed a fast and efficient count-based matrix factorization method, scNBMF, which is more powerful for detecting cell type purposes. A series of experiments were performed on three public scRNAseq data sets. The results show that scNBMF is a more powerful tool in large-scale scRNAseq data analysis. scNBMF was implemented in R and Python, and the source code are freely available at https://github.com/sqsun .
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