GAAS is an integrated software framework for efficient management, analysis and visualization of large amounts of gene expression data across replicated experiments. It is structured in management, analysis and visualization sections that allow dealing with several gene expression dataset formats, custom differential expression data analyses, suitable visualization, and storage of results.
The management section is based on a relational database system, allowing handling and analyzing gene expression data generated by different high-throughput array technologies, independently from storage formats. Besides, it ensures management and exportability of result data through custom templates defining formats of output databases where storing analysis results.
In the analysis section several sequential processing steps are performed: background and spot quality evaluation; background correction and data normalization; evaluation of differential gene expression in a single experiment (i.e. test vs. control condition); determination of gene regulation (i.e. significant differential gene expression) across multiple replica experiments.
In the visualization section, a graphical user interface enables to interactively navigate within numerical results of gene differential expressions and their graphical plots.
GAAS is designed for a multi-user environment, enabling each user to store its own parameter values used to perform the analyses, and define data visualization schema and format of the output data.
