MOTIVATION: Retrieval of information on biological processes from large-scale expression data is still a time-consuming task. An automated analysis utilizing all expression information would greatly increase our understanding of the samples under study. RESULTS: We describe here a novel method to obtain a functional analysis of complex gene expression data. Instead of applying a predefined expression threshold, Gene Ontology (GO) terms are weighted using the actual measured levels of expression of all associated genes. Based on this concept, the application GO-Mapper was developed to quantitatively link gene expression levels to GO-terms for multiple experiments in an automated way. The applicability of GO-Mapper was developed and validated on in house and public human microarray data and mouse SAGE data. We demonstrate that the GO-Mapper allows for interrelating relevant biological functions with the experiments under study. AVAILABILITY: The GO-Mapper application is free of charge available from our website.

*Algorithms, *Databases, Protein, *Natural Language Processing, Animals, Comparative Study, Documentation/methods, Gene Expression Profiling/*methods, Humans, Mice, Oligonucleotide Array Sequence Analysis/*methods, Proteins/*chemistry/classification/*metabolism, Research Support, Non-U.S. Gov't, Software, Structure-Activity Relationship, User-Computer Interface
dx.doi.org/10.1093/bioinformatics/bth293, hdl.handle.net/1765/13372
Bioinformatics
Free full text at PubMed
Erasmus MC: University Medical Center Rotterdam

Smid, M, & Dorssers, L.C.J. (2004). GO-Mapper: functional analysis of gene expression data using the expression level as a score to evaluate Gene Ontology terms. Bioinformatics, 20(16), 2618–2625. doi:10.1093/bioinformatics/bth293