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Microarray technology changed the landscape of contemporary life sciences by providing vast amounts of expression data. Researchers are building up repositories of experiment results with various conditions and samples which serve the scientific community as a precious resource. Ensuring that the sample is of high quality is of utmost importance to this effort. The task is complicated by the fact that in many cases datasets lack information concerning pre-experimental quality assessment. Transcription profiling of tissue samples may be invalidated by an error caused by heterogeneity of the material. The risk of tissue cross contamination is especially high in oncological studies, where it is often difficult to extract the sample. Therefore, there is a need of developing a method detecting tissue contamination in a post-experimental phase. We propose Microarray Inspector: customizable, user-friendly software that enables easy detection of samples containing mixed tissue types. The advantage of the tool is that it uses raw expression data files and analyses each array independently. In addition, the system allows the user to adjust the criteria of the analysis to conform to individual needs and research requirements. The final output of the program contains comfortable to read reports about tissue contamination assessment with detailed information about the test parameters and results. Microarray Inspector provides a list of contaminant biomarkers needed in the analysis of adipose tissue contamination. Using real data (datasets from public repositories) and our tool, we confirmed high specificity of the software in detecting contamination. The results indicated the presence of adipose tissue admixture in a range from approximately 4% to 13% in several tested surgical samples.

Microarray Inspector: tissue cross contamination detection tool for microarray data.