2009/10/04 Version 1.0 was released.
What is DynaMod?
DynaMod is a web?based application that identifies significant functional modules reflecting the change of modularity and differential expressions that are correlated with gene expression profiles under different conditions. DynaMod allows the inspection of a wide variety of functional modules such as the biological pathways, transcriptional factor-target gene groups, microRNA-target gene groups, protein complexes, and hub networks involved in protein interactome.
What are the DynaMod functionalities?
(1) Discovery of functional modules reflecting the changes of modularity: the statistical significance of a module score is scored by the corresponding P-value and false discovery rate (q-value) to z-test score. This toos provides a novel scoring strategy is introduced that uses the average mutual information (MI) differences of gene-pairs in predefined functional modules dependent on phenotypes. These scores show statistical normality with a much smaller sampling size compared to those of previous tools. This outstanding characteristic of the score guarantees a more adequate parametric analysis of gene set enrichment for functional modules having wide range of member size.
(2) Module expression activity (MEA): MEA is a score estimating the differential expression of a module and up-regulated group (Up_MEA) or down-regulated group (Down_MEA) of a module. MEA is given by the following equations.
(3) Significant test for individual genes and gene pairs: Although functional module-based analysis is the main goal, users may need occasionally the significance of individual genes. Dynamod evaluates the significance scores of individual genes by t-test or fold changes and provides the results. Dynamod also provides the significances of MI for individual gene-pairs.
(4) Network study among significant functional modules: Unions of the functional modules and neighbor modules are provided for all pairs of the significant functional modules, whose overlap score exceeds a specific threshold. Users can acquire the association among functional modules by genes and gene pairs representing significant MI difference in the overlap.
(5) Cross comparison between the analysis outputs: it is possible to perform a cross-comparison between the analysis outputs from two different datasets.
Example result of the DynaMod
This Glioblastoma dataset represents 23 non-glioblastoma samples and 81 glioblastoma samples.
It contains 54,613 probe genes.. [GEO]
Choong-Hyun Sun, Taeho Hwang, Kimin Oh, Gwan-Su Yi. DynaMod : dynamic fucntional modularity analysis. Nucleic Acids Res., 11 May 2010; In press. [ Access ]