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MultiDataSet: an R package for encapsulating multiple data sets with application to omic data integration.

Carles Hernandez-Ferrer1,2,3, Carlos Ruiz-Arenas1,2,3, Alba Beltran-Gomila1,2,3

  • 1Institut de Salut Global de Barcelona (ISGlobal) - Campus Mar, Barcelona Biulding: Biomedical Research Park, c/Dr. Aiguader, 88, 08003, Barcelona, Spain.

BMC Bioinformatics
|January 19, 2017
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Summary
This summary is machine-generated.

A new R class, MultiDataSet, manages diverse omic datasets from single subjects, simplifying data integration and analysis in biomedical research.

Keywords:
Data infrastructureData integrationData organizationOmics dataR

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Genomic assay costs have decreased, leading to large biomedical datasets and multi-experiment studies on the same subjects.
  • Existing Bioconductor packages manage individual experiments but lack a standard class for multi-omic datasets from the same subjects.
  • Current R/Bioconductor packages for biological data integration often use basic data structures without general methods for subsetting or sample selection.

Purpose of the Study:

  • To develop a standardized R class for managing and integrating diverse omic datasets from individual subjects.
  • To address the challenges of handling multiple, incomplete omic datasets.
  • To provide a unified framework for omic data integration and analysis within the R/Bioconductor environment.

Main Methods:

  • Development of the MultiDataSet R class, adhering to Bioconductor standards.
  • Implementation of methods for managing multiple and non-complete datasets.
  • Design of general subsetting and sample selection functionalities.

Main Results:

  • The MultiDataSet class effectively encapsulates multiple datasets.
  • It simplifies the management of complex, multi-omic data from single subjects.
  • Demonstrated utility in data integration analysis, development of new omic analysis methods, and encapsulation of novel biological data.

Conclusions:

  • MultiDataSet is a robust and suitable class for omic data integration within the R and Bioconductor ecosystem.
  • It provides a standardized approach to handling complex biological data, facilitating advanced analysis.