RAD (RNA abundance database): an infrastructure for array data analysis

Analysis of array-based gene expression experiments is challenging particularly when multiple experiments are involved and presents challenges in data management as well. Selecting well-measured spots and normalizing raw data are basic steps required for subsequent analyses, especially those involved with comparisons over a collection of experiments. Other preprocessing steps might also be needed for certain analyses. The most appropriate criteria for spot selection, for normalization, and for other data transformations depend on the experiments under study and on the questions investigated. Furthermore, comparing experiments appropriately requires knowledge of how the experiments were performed and the samples that were used in sufficient detail to understand their degree of similarity. Approaches taken in RAD to address these issues will be presented. These include the storage of raw and processed data along with history and parameter tracking and the use of ontologies to provide precise consistent experimental descriptions.

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