A relational schema for both array-based and SAGE gene expression experiments

A relational schema is described for capturing highly parallel gene express ion experiments using different technologies. This schema grew out of effor ts to build a database for collaborators working on different biological sy stems and using different types of platforms in their gene expression exper iments as well as different types of image quantification software. The tab les are conceptually organized into three categories of information: Platfo rm, Experiment (which includes image scanning and quantification), and Data . The strengths of the schema are: (i) integrating information on array ele ments using a gene index; (ii) describing samples using ontologies; (iii) r educing an experiment to a single RNA source for precise descriptions yet n ot losing the relationships between experiments done at the same time or fo r the same project; and (iv) maintaining both raw and processed (e.g, clean sed and normalized) data and recording how the data is processed. The resul t is a novel schema, which can hold both array and non-array data, is exten sible for detailed experimental descriptions that are precise and consisten t, and allows for meaningful comparisons of genes between experiments.