BBKNN: fast batch alignment of single cell transcriptomes

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ID: 304359
2019
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Abstract
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.
Reference Key
openalex_W2967177832 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Krzysztof Polański, Matthew D. Young, Zhichao Miao, Kerstin B. Meyer, Sarah A. Teichmann, Jong-Eun Park
Journal BMC Bioinformatics
Year 2019
DOI
10.1093/bioinformatics/btz625
URL
https://academic.oup.com/bioinformatics/article-pdf/36/3/964/32369783/btz625.pdf
Keywords Keywords not found

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