*omeSOM is a tool designed to give support to the data mining task of metabolic and transcriptional datasets derived from different databases. It provides a user-friendly interface and offers several visualization tools easy to understand by non-expert users. Therefore, *omeSOM is a tool designed to give support to the data mining task applied to basic research as well as breeding programs.
Main features
- Neurons painting according to type of data grouped (metabolite, transcripts or combined metabolite and transcripts); this way, neurons grouping integrated data together are quickly highlighted.
- Quality evaluation of clusters of combined data types.
- Setting of several possible visualization neighborhoods of a neuron for the easy detection of groups of combined data types, avoiding the need for a cluster identification procedure.
- Detail view of normalized and original values of each of the datapoints associated with a neuron.
- Graphical indication of gene expression levels and/or metabolite variation of grouped patterns.
- Markup of transcripts not expressed in an IL and missing data in metabolite measurements.
- KEGG pathways cross-reference.
- Unigene and arabidopsis annotations are provided for transcripts.
*omeSOM is oriented towards discovering unknown relationships between data, as well as providing simple visualizations for the identification of co-expressed genes and co-accumulated metabolites. A case study which involved gene expression measurements and metabolite profiles from tomato fruits is provided to show the application of the proposed tool. The interest in comparing the cultivated tomato against the different ILs lies on the fact that, as it has been proven, some wild tomato relatives can be sources of several agronomical characters which could be used for the improvement of commercial tomato lines.