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BBKNN: fast batch alignment of single cell transcriptomes

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 computationall...

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Detalles Bibliográficos
Autores principales: Polański, Krzysztof, Young, Matthew D, Miao, Zhichao, Meyer, Kerstin B, Teichmann, Sarah A, Park, Jong-Eun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9883685/
https://www.ncbi.nlm.nih.gov/pubmed/31400197
http://dx.doi.org/10.1093/bioinformatics/btz625
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author Polański, Krzysztof
Young, Matthew D
Miao, Zhichao
Meyer, Kerstin B
Teichmann, Sarah A
Park, Jong-Eun
author_facet Polański, Krzysztof
Young, Matthew D
Miao, Zhichao
Meyer, Kerstin B
Teichmann, Sarah A
Park, Jong-Eun
author_sort Polański, Krzysztof
collection PubMed
description 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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spelling pubmed-98836852023-02-01 BBKNN: fast batch alignment of single cell transcriptomes Polański, Krzysztof Young, Matthew D Miao, Zhichao Meyer, Kerstin B Teichmann, Sarah A Park, Jong-Eun Bioinformatics Applications Note 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. Oxford University Press 2019-08-10 /pmc/articles/PMC9883685/ /pubmed/31400197 http://dx.doi.org/10.1093/bioinformatics/btz625 Text en © The Author(s) 2019. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Applications Note
Polański, Krzysztof
Young, Matthew D
Miao, Zhichao
Meyer, Kerstin B
Teichmann, Sarah A
Park, Jong-Eun
BBKNN: fast batch alignment of single cell transcriptomes
title BBKNN: fast batch alignment of single cell transcriptomes
title_full BBKNN: fast batch alignment of single cell transcriptomes
title_fullStr BBKNN: fast batch alignment of single cell transcriptomes
title_full_unstemmed BBKNN: fast batch alignment of single cell transcriptomes
title_short BBKNN: fast batch alignment of single cell transcriptomes
title_sort bbknn: fast batch alignment of single cell transcriptomes
topic Applications Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9883685/
https://www.ncbi.nlm.nih.gov/pubmed/31400197
http://dx.doi.org/10.1093/bioinformatics/btz625
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