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“Omics” studies generate long lists of genes, proteins, metabolites or other features which can be difficult to decipher. Feature set enrichment analysis utilizing annotated groups/classes of features (such as pathways, gene ontology terms or gene/metabolic modules) can provide a powerful gateway to associate data to phenotypes such as disease process or treatment progression. At the same time, the increasing use of technologies to generate multidimensional omics data sets based on specific cell types or responses to stimuli increases the number and breadth of annotated feature sets available for enrichment analysis, facilitating the ability to draw biologically relevant conclusions. However, existing tools and applications for enrichment analysis are adapted specifically to gene set enrichment and lack functionalities to analyze rapidly growing amounts of metabolomics and other data. Moreover, such tools often provide only a limited range of statistical methods, rely on permutation tests, lack suitable visualization tools to facilitate result interpretation in complex experimental setups, and lack standalone versions usable in semi-automatized workflows. Here, we present tmod, an R package which implements powerful statistical methods for enrichment analysis. Tmod includes definitions of widely used feature sets for transcriptomic and metabolomic profiling and also allows use of custom user-provided feature sets. Moreover, it provides novel and intuitive visualiza- tion methods which facilitate interpretation of complex data sets. The implemented statistical tests allow the significance of enrichment within sorted feature lists to be calculated without randomization tests and thus are suitable for combining functional analysis with multivariate techniques.
tmod combines state of the art approaches to variable set enrichment tests with novel visualizations and analytical statistical solutions. Furthermore, tmod allows a seamless integration with limma as well as multivariate techniques, and includes gene sets and metabolite sets for a rapid analysis of transcriptomic and metabolomic data.
tmod source package (R language)
The R source package containing tmod sources as well as the associated data sets.