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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
Descripción
Sumario: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.