GEDI: a user-friendly toolbox for analysis of large-scale gene expression data

Here, we introduce an user-friendly toolbox called GEDI (Gene Expression Data Interpreter), an extensible, open-source, and freely-available tool that we believe will be useful to a wide range of laboratories, and to researchers with no background in Mathematics and Computer Science, allowing them to analyze their own data by applying both classical and advanced approaches developed and recently published by Fujita et al.GEDI is an integrated user-friendly viewer that combines the state of the art SVR, DVAR and SVAR algorithms, previously developed by us. It facilitates the application of SVR, DVAR and SVAR, further than the mathematical formulas present in the corresponding publications, and allows one to better understand the results by means of available visualizations. Both running the statistical methods and visualizing the results are carried out within the graphical user interface, rendering these algorithms accessible to the broad community of researchers in Molecular Biology.High-throughput DNA microarray technologies yield up to tens of thousands of gene expression data, which are useful to identify differentially expressed genes, biomarkers and molecular disease profiles. In recent years, microarray platforms have become available at relatively low costs, becoming more popular among research groups which are interested in gene expression analysis. On the other hand, much effort has been spent in developing improved methods to analyze the data derived from these microarrays. These methods involve advanced mathematical and statistical models, which are quite cumbersome to biomedical researchers who attempt to implement these methods. Due to this difficulty, some of these advanced methods are often abandoned and data analysis is carried out using only the classical methods, which are implemented in popular statistical softwares. An user-friendly software could make it possible to use recently developed methods to integrate, qualify, and infer biological insi