Research article

A proposed metric for assessing the measurement quality of individual microarrays

Kyoungmi Kim¹ , Grier P Page¹ , T Mark Beasley¹ , Stephen Barnes² , Katherine E Scheirer³ and David B Allison¹

¹Department of Biostatistics, Section on Statistical Genetics, University of Alabama at Birmingham, Birmingham, Alabama, USA

²Department of Pharmacology and Toxicology, University of Alabama at Birmingham, Birmingham, Alabama, USA

³Heflin Center for Human Genetics, University of Alabama at Birmingham, Birmingham, Alabama, USA

author email corresponding author email

BMC Bioinformatics 2006, 7:35doi:10.1186/1471-2105-7-35

Published:	23 January 2006

Abstract

Background

High-density microarray technology is increasingly applied to study gene expression levels on a large scale. Microarray experiments rely on several critical steps that may introduce error and uncertainty in analyses. These steps include mRNA sample extraction, amplification and labeling, hybridization, and scanning. In some cases this may be manifested as systematic spatial variation on the surface of microarray in which expression measurements within an individual array may vary as a function of geographic position on the array surface.

Results

We hypothesized that an index of the degree of spatiality of gene expression measurements associated with their physical geographic locations on an array could indicate the summary of the physical reliability of the microarray. We introduced a novel way to formulate this index using a statistical analysis tool. Our approach regressed gene expression intensity measurements on a polynomial response surface of the microarray's Cartesian coordinates. We demonstrated this method using a fixed model and presented results from real and simulated datasets.

Conclusion

We demonstrated the potential of such a quantitative metric for assessing the reliability of individual arrays. Moreover, we showed that this procedure can be incorporated into laboratory practice as a means to set quality control specifications and as a tool to determine whether an array has sufficient quality to be retained in terms of spatial correlation of gene expression measurements.