GOurmet: A tool for quantitative comparison and visualization of gene expression profiles based on gene ontology (GO) distributions |
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| Authors: | Jason M Doherty Lynn K Carmichael Jason C Mills |
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| Institution: | (1) Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO 63110, USA;(2) Departments of Molecular Biology and Pharmacology, Washington University School of Medicine, St. Louis, MO 63110, USA;(3) The Genome Sequencing Center, Washington University School of Medicine, St. Louis, MO 63110, USA |
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| Abstract: | Background The ever-expanding population of gene expression profiles (EPs) from specified cells and tissues under a variety of experimental
conditions is an important but difficult resource for investigators to utilize effectively. Software tools have been recently
developed to use the distribution of gene ontology (GO) terms associated with the genes in an EP to identify specific biological
functions or processes that are over- or under-represented in that EP relative to other EPs. Additionally, it is possible
to use the distribution of GO terms inherent to each EP to relate that EP as a whole to other EPs. Because GO term annotation
is organized in a tree-like cascade of variable granularity, this approach allows the user to relate (e.g., by hierarchical clustering) EPs of varying length and from different platforms (e.g., GeneChip, SAGE, EST library). |
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