MASQOT: a method for cDNA microarray spot quality control

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

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

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

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

author email corresponding author email

BMC Bioinformatics 2005, 6:250doi: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.