Abstract

BackgroundAlthough DNA microarray technologies are very powerful for the simultaneous quantitative characterization of thousands of genes, the quality of the obtained experimental data is often far from ideal. The measured microarrays images represent a regular collection of spots, and the intensity of light at each spot is proportional to the DNA copy number or to the expression level of the gene whose DNA clone is spotted. Spot quality control is an essential part of microarray image analysis, which must be carried out at the level of individual spot identification. The problem is difficult to formalize due to the diversity of instrumental and biological factors that can influence the result.ResultsFor each spot we estimate the ratio of measured fluorescence intensities revealing differential gene expression or change in DNA copy numbers between the test and control samples. We also define a set of quality characteristics and a model for combining these characteristics into an overall spot quality value. We have developed a training procedure to evaluate the contribution of each individual characteristic in the overall quality. This procedure uses information available from replicated spots, located in the same array or over a set of replicated arrays. It is assumed that unspoiled replicated spots must have very close ratios, whereas poor spots yield greater diversity in the obtained ratio estimates.ConclusionThe developed procedure provides an automatic tool to quantify spot quality and to identify different types of spot deficiency occurring in DNA microarray technology. Quality values assigned to each spot can be used either to eliminate spots or to weight contribution of each ratio estimate in follow-up analysis procedures.

Highlights

  • DNA microarray technologies are very powerful for the simultaneous quantitative characterization of thousands of genes, the quality of the obtained experimental data is often far from ideal

  • In comparative DNA microarray experiments compared test and control samples are labeled with different fluorescent dyes, mixed up and co-hybridized with the DNA clones regularly spotted on the microarray

  • Software The developed algorithm for quality control is included in the software package MAIA, which offers a complete solution for DNA microarray image analysis, including automatic spot localization and spot quantification procedures

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Summary

Introduction

DNA microarray technologies are very powerful for the simultaneous quantitative characterization of thousands of genes, the quality of the obtained experimental data is often far from ideal. The measured microarrays images represent a regular collection of spots, and the intensity of light at each spot is proportional to the DNA copy number or to the expression level of the gene whose DNA clone is spotted. The ratio of the measured intensities (Cy5/ Cy3) for each microarray spot reveals either differential gene expression (cDNA technology [1]) or change in DNA copy numbers (comparative genome hybridization (CGH) technology [2]) between the test and control samples for the corresponding gene. A number of parameters characterizing the spot, such as signal-to-noise ratio, size, circularity, etc., are introduced. These parameters have to be combined into an overall quality value to be used as a confidence level in the follow-up analysis. In two studies [5,6], it was assumed that individual quality scores contribute equivalently to the composite quality score

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