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Title: MultiDataSet: an R package for encapsulating multiple data sets with application to omic data integration
Author: Hernández Ferrer, Carles
Ruiz Arenas, Carlos
Beltran Gomila, Alba
González, Juan R.
Keywords: Processament de dades
Dades massives
Data processing
Big data
Issue Date: 17-Jan-2017
Publisher: BioMed Central
Abstract: BACKGROUND: Reduction in the cost of genomic assays has generated large amounts of biomedical-related data. As a result, current studies perform multiple experiments in the same subjects. While Bioconductor's methods and classes implemented in different packages manage individual experiments, there is not a standard class to properly manage different omic datasets from the same subjects. In addition, most R/Bioconductor packages that have been designed to integrate and visualize biological data often use basic data structures with no clear general methods, such as subsetting or selecting samples. RESULTS: To cover this need, we have developed MultiDataSet, a new R class based on Bioconductor standards, designed to encapsulate multiple data sets. MultiDataSet deals with the usual difficulties of managing multiple and non-complete data sets while offering a simple and general way of subsetting features and selecting samples. We illustrate the use of MultiDataSet in three common situations: 1) performing integration analysis with third party packages; 2) creating new methods and functions for omic data integration; 3) encapsulating new unimplemented data from any biological experiment. CONCLUSIONS: MultiDataSet is a suitable class for data integration under R and Bioconductor framework.
Note: Reproducció del document publicat a:
It is part of: BMC Bioinformatics, 2017, vol. 18, num. 36
Related resource:
ISSN: 1471-2105
Appears in Collections:Articles publicats en revistes (ISGlobal)

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