TRANSCRIPTOME 2002: From Functional Genomics to Systems Biology
March 10-13, 2002
Seattle, Washington, USA

P-55

SAGEdb: A Computational Platform for Investigations Using Serial Analysis of Gene Expression

Richard Varhol, Scott Zuyderduyn, Mehrdad Oveisi-Fordoei, Erin Garland, Martin Krzywinski, Marco Marra and Steven Jones, Genome Sequence Centre BC Cancer Agency, Vancouver, CANADA

Serial Analysis of Gene Expression, SAGE, a comprehensive gene expression profiling technique, generates acurate profiles of mRNA populations, making biological inferences from such expression data remains challenging. Our goal is to provide a platform facilitating the analysis and characterization of SAGE data. An important characteristic of our effort is the exploitation of existing connections between disparate data sources.  This has been accomplished by developing a relational database containing large amounts of both public and internally generated biological information. These data include raw nucleotide and protein sequences, biological pathways, protein models, disease information, molecular interactions and tissue specificity.  Where no connection exists, similarity is inferred computationally using BLAST & HMM. Emphasis is currently placed on designing effective methods to add new data sources and update existing data sources with new information. A complementary software package, SAGEspace, provides statistical analysis of raw data, allowing rapid formation of biological questions and enabling investigators to visualize and interpret results. An example of the software’s capabilities involves modeling a pair-wise SAGE library comparison in 3D space.  Gene expression levels are represented on the x-y axes; the degeneracy of a particular data point is represented on the z-axis; and results of statistical analyses and biological questions are denoted by colour, shape and texture.


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