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1 Department of Physiological Sciences, Oklahoma State University, Stillwater, OK, USA
* To whom correspondence should be addressed. E-mail: liulin{at}okstate.edu.
The spot images from DNA microarray highly affect the discovery of biological knowledge from gene expression data. However, results from quality analysis, normalization, differential expression, and cluster analysis are rarely validated with spot images in current data analysis methods or software packages. We designed RealSpot, a software package, to validate the results by directly associating spot quality and data with spot images in a spreadsheet table. RealSpot splits hybridization images into individual spots stored in a spreadsheet table. It subsequently associates microarray data with spot images and performs data validation through the standard table operation such as sorting, searching, and editing. RealSpot has several builtin functions to facilitate data validation, including spot quality analysis, data organization, one-way ANOVA, gene ontology association, verification, import, and export. We used RealSpot to evaluate 77 slides (30,000 features each) from real hybridization experiments, and to validate results from each step of data analysis. It took about 10 min to validate results of spot quality after initial evaluation and correct ~ 0.3% of falsely assigned qualities of 10K spots. We validated 1,641 of 2,110 differentially expressed genes identified by SAM analysis in about half an hour by comparing each gene with its respective spot image. Furthermore, we found 6 of 48 genes in one cluster from k-mean clustering method showed inconsistent trends of spot images. RealSpot is efficient for validating microarray results and thus helpful for improving the reliability of the whole microarray experiment for experimentalists.
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