BBKNN: fast batch alignment of single cell transcriptomes.

> 商业许可源文 · EUROPE_PMC · [CC-BY](https://creativecommons.org/licenses/by/)

书目信息

引用：Polański K, Young MD, Miao Z, Meyer KB, Teichmann SA, Park JE. (2020). BBKNN: fast batch alignment of single cell transcriptomes. Bioinformatics (Oxford, England). PMID 31400197 · PMC9883685 · DOI 10.1093/bioinformatics/btz625

证据类型：PRIMARY_RESEARCH

主题：rna-seq、single-cell

被引次数（采集时）：756

原始记录：[Europe PMC](https://europepmc.org/article/MED/31400197)

来源许可：[CC-BY](https://creativecommons.org/licenses/by/)

作者摘要（按来源许可复用）

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.

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