Abstract
BackgroundLarge data sets from gene expression array studies are publicly available offering information highly valuable for research across many disciplines ranging from fundamental to clinical research. Highly advanced bioinformatics tools have been made available to researchers, but a demand for user-friendly software allowing researchers to quickly extract expression information for multiple genes from multiple studies persists.FindingsHere, we present a user-friendly LabVIEW program to automatically extract gene expression data for a list of genes from multiple normalized microarray datasets. Functionality was tested for 288 class A G protein-coupled receptors (GPCRs) and expression data from 12 studies comparing normal and diseased human hearts. Results confirmed known regulation of a beta 1 adrenergic receptor and further indicate novel research targets.ConclusionsAlthough existing software allows for complex data analyses, the LabVIEW based program presented here, “Array Data Extractor (ADE)”, provides users with a tool to retrieve meaningful information from multiple normalized gene expression datasets in a fast and easy way. Further, the graphical programming language used in LabVIEW allows applying changes to the program without the need of advanced programming knowledge.
Highlights
Large data sets from gene expression array studies are publicly available offering information highly valuable for research across many disciplines ranging from fundamental to clinical research
Conclusions: existing software allows for complex data analyses, the LabVIEW based program presented here, “Array Data Extractor (ADE)”, provides users with a tool to retrieve meaningful information from multiple normalized gene expression datasets in a fast and easy way
The graphical programming language used in LabVIEW allows applying changes to the program without the need of advanced programming knowledge
Summary
We introduce an easy-to-use software tool to extract and analyze normalized expression data This program provides researchers with a tool to analyze gene array data utilizing publicly available normalized expression data. Beyond this scope, far more sophisticated tools (cited above) may be used for more detailed analysis. – If ADE reports that it can’t open a file, be sure the format of files is correct (.txt), and/or use sample files provided to test. – Moving Data folders between Mac and Windows systems may cause problems. Sample files include three data files downloaded from the GEO database [30,31] With these files ADE can be directly tested without further modification.
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