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.
MultiDataSet is a new R class based on Bioconductor standards, designed to encapsulate multiple data sets. It 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. This paper illustrates the use of MultiDataSet in: performing integration analysis with third party packages; creating new methods and functions for omic data integration; encapsulating new unimplemented data from any biological experiment.
You can download the publication here: MultiDataSet: an R package for encapsulating multiple data sets with application to omic data integration