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Open Access Methodology article

MASQOT: a method for cDNA microarray spot quality control

Max Bylesjö1*, Daniel Eriksson2, Andreas Sjödin3, Michael Sjöström1, Stefan Jansson3, Henrik Antti1 and Johan Trygg1

Author Affiliations

1 Research group for Chemometrics, Department of Chemistry, Umeå University, SE-901 87 Umeå, Sweden

2 Umeå Plant Science Centre, Department of Forest Genetics and Plant Physiology, Swedish University of Agricultural Sciences, SE-901 83 Umeå, Sweden

3 Umeå Plant Science Centre, Department of Plant Physiology, Umeå University, SE-901 87 Umeå, Sweden

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BMC Bioinformatics 2005, 6:250  doi:10.1186/1471-2105-6-250

Published: 13 October 2005

Abstract

Background

cDNA microarray technology has emerged as a major player in the parallel detection of biomolecules, but still suffers from fundamental technical problems. Identifying and removing unreliable data is crucial to prevent the risk of receiving illusive analysis results. Visual assessment of spot quality is still a common procedure, despite the time-consuming work of manually inspecting spots in the range of hundreds of thousands or more.

Results

A novel methodology for cDNA microarray spot quality control is outlined. Multivariate discriminant analysis was used to assess spot quality based on existing and novel descriptors. The presented methodology displays high reproducibility and was found superior in identifying unreliable data compared to other evaluated methodologies.

Conclusion

The proposed methodology for cDNA microarray spot quality control generates non-discrete values of spot quality which can be utilized as weights in subsequent analysis procedures as well as to discard spots of undesired quality using the suggested threshold values. The MASQOT approach provides a consistent assessment of spot quality and can be considered an alternative to the labor-intensive manual quality assessment process.