Multiple Co-inertia Analysis of Multiple OMICS Data using omicade4

Multivariate approaches have been applied successfully in the analysis of high throughput ”omics”data. Principal component analysis (PCA) has been shown to be useful in exploratory analysis of linear trends in biological data [1]. Culhane and colleagues employed a two table coupling method (co-inertia analysis, CIA) to examine covariant gene expression patterns between microarray datasets from two different platforms [2]. Although PCA is available in several R packages, the ade4 and made4 contain many additional multivariate statistical methods including methods for analysis of one data table, coupling of two data tables or multi-table analysis [3, 4]. These methods for integrating multiple datasets make these particular packages very attractive for analysis of multi-omics data. omicade4 is developed as an extension to ade4 and made4 to facilitate input and analysis of more than two omics datasets.