Microarray Inspector: tissue cross contamination detection tool for microarray data

Area of Science:

• Genomics
• Bioinformatics
• Molecular Biology

Background:

• Microarray technology generates vast expression data, crucial for life sciences research.
• High sample quality is essential, but pre-experimental quality assessment is often missing.
• Tissue heterogeneity and cross-contamination, especially in oncological studies, can invalidate transcription profiling data.

Purpose of the Study:

• To develop a post-experimental method for detecting tissue contamination in microarray datasets.
• To introduce Microarray Inspector, a user-friendly software for identifying mixed tissue samples.

Main Methods:

• Microarray Inspector analyzes raw expression data files independently for each array.
• The software allows users to customize analysis criteria based on research needs.
• It identifies contaminant biomarkers, specifically for adipose tissue contamination.

Main Results:

• The software demonstrated high specificity in detecting contamination using real-world public datasets.
• Adipose tissue admixture was detected in 4% to 13% of tested surgical samples.
• The tool provides detailed reports on contamination assessment, including test parameters and results.

Conclusions:

• Microarray Inspector is an effective tool for detecting tissue contamination in post-experimental phases.
• The software enhances the reliability of microarray-based research by ensuring sample quality.
• Customizable analysis and user-friendly reports make it a valuable resource for the scientific community.