Making sense of microarray data : development of an integrated bioinformatics tool

Microarray technology promises to monitor interactions among tens of thousands of genes simultaneously. Two types of microarrays, Oligonucleotide (oligo) and cDNA arrays, are in common use. Oligo arrays have the advantage of providing a platform that can be more readily compared between laboratories. With rapid evolution of hardware and lab protocols, the challenge becomes the analysis of a vast amount of data rather than the manufacture or the use of microarrays. Most software applications were developed dealing with cDNA arrays. There remains a lack of tools that can be used for oligo array analysis. The goal of this research project is to develop a bioinformatics tool dedicated to analyzing oligo array data. Our tool, AffyMiner, consists of three functional components: GeneFinding---finding significant genes in the experiment, GOTree---constructing a Gene Ontology (GO) tree, and interfaces---linking to third-party applications. AffyMiner effectively deals with multiple replicates in the experiment, provides users flexibility of choosing different data metrics for finding significant genes, and is capable of incorporating various gene annotations. In addition, AffyMiner maps genes of interest onto the GO spaces, providing assistance in the interpretation of findings in the context of biology. Furthermore, AffyMiner provides a portal to use Cluster and GenMAPP, two popular programs for microarray analysis. AffyMiner has been used by multiple users and was found to be an effective tool that has reduced plenty of time and efforts needed for data analysi