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Development and application of a microarray meter tool to optimize microarray experiments

Richard JD Rouse12, Katrine Field1, Jennifer Lapira1, Allen Lee1, Ivan Wick1, Colleen Eckhardt1, C Ramana Bhasker3, Laura Soverchia14 and Gary Hardiman15*

Author Affiliations

1 Biomedical Genomics Microarray Facility (BIOGEM), La Jolla CA 92093, USA

2 HTS Resources, LLC, 11175-A Flintkote Avenue, San Diego, CA 92121, USA

3 Center for Molecular Genetics, Department of Pediatrics, School of Medicine, University of California, San Diego, La Jolla, CA 92093-0634, USA

4 Department of Experimental Medicine and Public Health, University of Camerino, 62032 Camerino (MC), Italy

5 Department of Medicine, University of California San Diego, La Jolla, CA 92093-0724, USA

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BMC Research Notes 2008, 1:45  doi:10.1186/1756-0500-1-45

Published: 11 July 2008



Successful microarray experimentation requires a complex interplay between the slide chemistry, the printing pins, the nucleic acid probes and targets, and the hybridization milieu. Optimization of these parameters and a careful evaluation of emerging slide chemistries are a prerequisite to any large scale array fabrication effort. We have developed a 'microarray meter' tool which assesses the inherent variations associated with microarray measurement prior to embarking on large scale projects.


The microarray meter consists of nucleic acid targets (reference and dynamic range control) and probe components. Different plate designs containing identical probe material were formulated to accommodate different robotic and pin designs. We examined the variability in probe quality and quantity (as judged by the amount of DNA printed and remaining post-hybridization) using three robots equipped with capillary printing pins.


The generation of microarray data with minimal variation requires consistent quality control of the (DNA microarray) manufacturing and experimental processes. Spot reproducibility is a measure primarily of the variations associated with printing. The microarray meter assesses array quality by measuring the DNA content for every feature. It provides a post-hybridization analysis of array quality by scoring probe performance using three metrics, a) a measure of variability in the signal intensities, b) a measure of the signal dynamic range and c) a measure of variability of the spot morphologies.