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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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2019
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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. |
format | Online Article Text |
id | pubmed-9883685 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
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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