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HDCytoData: Collection of high-dimensional cytometry benchmark datasets in Bioconductor object formats

Benchmarking is a crucial step during computational analysis and method development. Recently, a number of new methods have been developed for analyzing high-dimensional cytometry data. However, it can be difficult for analysts and developers to find and access well-characterized benchmark datasets....

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Detalles Bibliográficos
Autores principales: Weber, Lukas M., Soneson, Charlotte
Formato: Online Artículo Texto
Lenguaje:English
Publicado: F1000 Research Limited 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6904983/
https://www.ncbi.nlm.nih.gov/pubmed/31857895
http://dx.doi.org/10.12688/f1000research.20210.2
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author Weber, Lukas M.
Soneson, Charlotte
author_facet Weber, Lukas M.
Soneson, Charlotte
author_sort Weber, Lukas M.
collection PubMed
description Benchmarking is a crucial step during computational analysis and method development. Recently, a number of new methods have been developed for analyzing high-dimensional cytometry data. However, it can be difficult for analysts and developers to find and access well-characterized benchmark datasets. Here, we present HDCytoData, a Bioconductor package providing streamlined access to several publicly available high-dimensional cytometry benchmark datasets. The package is designed to be extensible, allowing new datasets to be contributed by ourselves or other researchers in the future. Currently, the package includes a set of experimental and semi-simulated datasets, which have been used in our previous work to evaluate methods for clustering and differential analyses. Datasets are formatted into standard SummarizedExperiment and flowSet Bioconductor object formats, which include complete metadata within the objects. Access is provided through Bioconductor's ExperimentHub interface. The package is freely available from http://bioconductor.org/packages/HDCytoData.
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spelling pubmed-69049832019-12-18 HDCytoData: Collection of high-dimensional cytometry benchmark datasets in Bioconductor object formats Weber, Lukas M. Soneson, Charlotte F1000Res Software Tool Article Benchmarking is a crucial step during computational analysis and method development. Recently, a number of new methods have been developed for analyzing high-dimensional cytometry data. However, it can be difficult for analysts and developers to find and access well-characterized benchmark datasets. Here, we present HDCytoData, a Bioconductor package providing streamlined access to several publicly available high-dimensional cytometry benchmark datasets. The package is designed to be extensible, allowing new datasets to be contributed by ourselves or other researchers in the future. Currently, the package includes a set of experimental and semi-simulated datasets, which have been used in our previous work to evaluate methods for clustering and differential analyses. Datasets are formatted into standard SummarizedExperiment and flowSet Bioconductor object formats, which include complete metadata within the objects. Access is provided through Bioconductor's ExperimentHub interface. The package is freely available from http://bioconductor.org/packages/HDCytoData. F1000 Research Limited 2019-12-04 /pmc/articles/PMC6904983/ /pubmed/31857895 http://dx.doi.org/10.12688/f1000research.20210.2 Text en Copyright: © 2019 Weber LM and Soneson C http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Software Tool Article
Weber, Lukas M.
Soneson, Charlotte
HDCytoData: Collection of high-dimensional cytometry benchmark datasets in Bioconductor object formats
title HDCytoData: Collection of high-dimensional cytometry benchmark datasets in Bioconductor object formats
title_full HDCytoData: Collection of high-dimensional cytometry benchmark datasets in Bioconductor object formats
title_fullStr HDCytoData: Collection of high-dimensional cytometry benchmark datasets in Bioconductor object formats
title_full_unstemmed HDCytoData: Collection of high-dimensional cytometry benchmark datasets in Bioconductor object formats
title_short HDCytoData: Collection of high-dimensional cytometry benchmark datasets in Bioconductor object formats
title_sort hdcytodata: collection of high-dimensional cytometry benchmark datasets in bioconductor object formats
topic Software Tool Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6904983/
https://www.ncbi.nlm.nih.gov/pubmed/31857895
http://dx.doi.org/10.12688/f1000research.20210.2
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