BBKNN: fast batch alignment of single cell transcriptomes

• DOI: 10.1093/bioinformatics/btz625
• Publication Date: 2019-08-08T11:35:30Z
• Authors: Krzysztof Polański; Matthew D Young; Zhichao Miao; Kerstin B Meyer; Sarah A Teichmann; Jong-Eun Park
• Keywords: 0301 basic medicine; Applications Note; Mice; 03 medical and health sciences; Exome Sequencing; Animals; RNA-Seq; Transcriptome; Algorithms

Abstract

Motivation Increasing numbers of large scale single cell RNA-Seq projects are leading to a data explosion, which can only be fully exploited through data integration. A number of methods have been developed to combine diverse datasets by removing technical batch effects, but most are computationally intensive. To overcome the challenge of enormous datasets, we have developed BBKNN, an extremely fast graph-based data integration algorithm. We illustrate the power of BBKNN on large scale mouse atlasing data, and favourably benchmark its run time against a number of competing methods.

Availability and implementation BBKNN is available at https://github.com/Teichlab/bbknn, along with documentation and multiple example notebooks, and can be installed from pip.

Supplementary information Supplementary data are available at Bioinformatics online.