UIPBC: An effective clustering for scRNA-seq data analysis without user input

作者：

Highlights：

• This paper proposes a user input free clustering method for scRNA-seq data.

• The method does not depend on any specific cluster validity index.

• Results show its superiority in terms of discovering true cell groups.

• Datasets and source code are available as an R package.

摘要

•This paper proposes a user input free clustering method for scRNA-seq data.•The method does not depend on any specific cluster validity index.•Results show its superiority in terms of discovering true cell groups.•Datasets and source code are available as an R package.

论文关键词：scRNA-seq,Clustering,Next generation sequencing,Computational biology,Bioinformatics

论文评审过程：Received 24 October 2021, Revised 16 March 2022, Accepted 5 April 2022, Available online 22 April 2022, Version of Record 6 May 2022.

论文官网地址：https://doi.org/10.1016/j.knosys.2022.108767