title: A relational schema for both array-based and SAGE gene expression experiments.
abstract: A relational schema is described for capturing highly parallel gene expression experiments using different technologies. This schema grew out of efforts to build a database for collaborators working on different biological systems and using different types of platforms in their gene expression experiments as well as different types of image quantification software. The tables are conceptually organized into three categories of information: Platform, Experiment (which includes image scanning and quantification), and Data. The strengths of the schema are: (i) integrating information on array elements using a gene index; (ii) describing samples using ontologies; (iii) reducing an experiment to a single RNA source for precise descriptions yet not losing the relationships between experiments done at the same time or for the same project; and (iv) maintaining both raw and processed (e.g. cleansed and normalized) data and recording how the data is processed. The result is a novel schema, which can hold both array and non-array data, is extensible for detailed experimental descriptions that are precise and consistent, and allows for meaningful comparisons of genes between experiments.
authors: Computational Biology and Informatics Laboratory, Center for Bioinformatics, University of Pennsylvania, 1313 Blockley Hall, 418 Guardian Drive, Philadelphia, PA 19104-6021, USA.
authors: C
authors: C
authors: Stoeckert
authors: A
authors: A
authors: Pizarro
authors: E
authors: E
authors: Manduchi
authors: M
authors: M
authors: Gibson
authors: B
authors: B
authors: Brunk
authors: J
authors: J
authors: Crabtree
authors: J
authors: J
authors: Schug
authors: S
authors: S
authors: Shen-Orr
authors: G C
authors: GC
authors: Overton
mesh_terms: D016208:Databases, Factual; D015870:Gene Expression; D020411:Oligonucleotide Array Sequence Analysis