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

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

Matemàtiques a partir de la fotografia. Proposta i anàlisi d'activitats

[cat] En el present treball s’ha pretès analitzar com la fotografia és un material contextualitzat vàlid per desenvolupar activitats competencials de matemàtiques a l’educació secundària obligatòria. En la primera part s’ha estudiat la situació actual de les experiències didàctiques que fan ús de la fotografia dins l’àmbit matemàtic. Aquest ha estat el marc teòric que ha permès establir uns criteris per configurar i avaluar la proposta didàctica que s’ha presentat. En la segona part s’ha descrit la proposta didàctica en forma d’activitats que cobreixen continguts de cada un dels blocs del currículum de secundària. S’ha realitzat un recull d’activitats, detallades amb guies pel professorat i per l’alumnat, que puguin ser útils en un futur. De cada activitat s’ha realitzat una observació i una valoració didàctica. El resultat d’aquest treball ha estat una proposta educativa que analitza un recurs contextualitzat per treballar matemàtiques dins les aules de secundària

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

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

Additional file 1: of MultiDataSet: an R package for encapsulating multiple data sets with application to omic data integration

“Using MultiDataSet with third party R packages”. This file illustrates how to perform an integration analysis using multivariate co-inertia analysis (omicade4) and clustering of multiples tables (iClusterPlus). (ZIP 38 kb

Additional file 3: of MultiDataSet: an R package for encapsulating multiple data sets with application to omic data integration

“Adding a new type of data to MultiDataSet objects”. This file exemplifies how to create a method to incorporate data from S4 classes to a MultiDataSet object. (HTML 66 kb