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matter: an R package for rapid prototyping with larger-than-memory datasets on disk

SUMMARY: We introduce matter, an R package for direct interactions with larger-than-memory datasets, stored in an arbitrary number of files of any size. matter is primarily designed for datasets in new and rapidly evolving file formats, which may lack extensive software support. matter enables a wid...

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Detalles Bibliográficos
Autores principales: Bemis, Kylie A, Vitek, Olga
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5870624/
https://www.ncbi.nlm.nih.gov/pubmed/28633357
http://dx.doi.org/10.1093/bioinformatics/btx392
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author Bemis, Kylie A
Vitek, Olga
author_facet Bemis, Kylie A
Vitek, Olga
author_sort Bemis, Kylie A
collection PubMed
description SUMMARY: We introduce matter, an R package for direct interactions with larger-than-memory datasets, stored in an arbitrary number of files of any size. matter is primarily designed for datasets in new and rapidly evolving file formats, which may lack extensive software support. matter enables a wide variety of data exploration and manipulation steps and is extensible to many bioinformatics applications. It supports reproducible research by minimizing the need of converting and storing data in multiple formats. We illustrate the performance of matter in conjunction with the Bioconductor package Cardinal for analysis of high-resolution, high-throughput mass spectrometry imaging experiments. AVAILABILITY AND IMPLEMENTATION: The package, vignettes and examples of applications in several areas of bioinformatics are available open-source at www.bioconductor.org under the Artistic-2.0 license.
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spelling pubmed-58706242018-04-05 matter: an R package for rapid prototyping with larger-than-memory datasets on disk Bemis, Kylie A Vitek, Olga Bioinformatics Applications Notes SUMMARY: We introduce matter, an R package for direct interactions with larger-than-memory datasets, stored in an arbitrary number of files of any size. matter is primarily designed for datasets in new and rapidly evolving file formats, which may lack extensive software support. matter enables a wide variety of data exploration and manipulation steps and is extensible to many bioinformatics applications. It supports reproducible research by minimizing the need of converting and storing data in multiple formats. We illustrate the performance of matter in conjunction with the Bioconductor package Cardinal for analysis of high-resolution, high-throughput mass spectrometry imaging experiments. AVAILABILITY AND IMPLEMENTATION: The package, vignettes and examples of applications in several areas of bioinformatics are available open-source at www.bioconductor.org under the Artistic-2.0 license. Oxford University Press 2017-10-01 2017-06-15 /pmc/articles/PMC5870624/ /pubmed/28633357 http://dx.doi.org/10.1093/bioinformatics/btx392 Text en © The Author 2017. Published by Oxford University Press. http://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/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Applications Notes
Bemis, Kylie A
Vitek, Olga
matter: an R package for rapid prototyping with larger-than-memory datasets on disk
title matter: an R package for rapid prototyping with larger-than-memory datasets on disk
title_full matter: an R package for rapid prototyping with larger-than-memory datasets on disk
title_fullStr matter: an R package for rapid prototyping with larger-than-memory datasets on disk
title_full_unstemmed matter: an R package for rapid prototyping with larger-than-memory datasets on disk
title_short matter: an R package for rapid prototyping with larger-than-memory datasets on disk
title_sort matter: an r package for rapid prototyping with larger-than-memory datasets on disk
topic Applications Notes
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5870624/
https://www.ncbi.nlm.nih.gov/pubmed/28633357
http://dx.doi.org/10.1093/bioinformatics/btx392
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