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Optimization and clinical validation of a pathogen detection microarray

Christopher W Wong1*, Charlie Lee Wah Heng2, Leong Wan Yee1, Shirlena WL Soh3, Cissy B Kartasasmita4, Eric AF Simoes5, Martin L Hibberd3, Wing-Kin Sung2 and Lance D Miller1

Author Affiliations

1 Genomic Technologies, Genome Institute of Singapore, Republic of Singapore

2 Computational and Mathematical Biology, Genome Institute of Singapore, Republic of Singapore

3 Infectious Diseases, Genome Institute of Singapore, Republic of Singapore

4 Hasan Sadikin Hospital, Department of Pediatrics, Faculty of Medicine Universitas Padjadjaran, Indonesia

5 Section of Infectious Diseases, The University of Colorado at Denver and Health Sciences Center and The Children's Hospital, Denver, CO 80262, USA

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Genome Biology 2007, 8:R93  doi:10.1186/gb-2007-8-5-r93

Published: 28 May 2007


DNA microarrays used as 'genomic sensors' have great potential in clinical diagnostics. Biases inherent in random PCR-amplification, cross-hybridization effects, and inadequate microarray analysis, however, limit detection sensitivity and specificity. Here, we have studied the relationships between viral amplification efficiency, hybridization signal, and target-probe annealing specificity using a customized microarray platform. Novel features of this platform include the development of a robust algorithm that accurately predicts PCR bias during DNA amplification and can be used to improve PCR primer design, as well as a powerful statistical concept for inferring pathogen identity from probe recognition signatures. Compared to real-time PCR, the microarray platform identified pathogens with 94% accuracy (76% sensitivity and 100% specificity) in a panel of 36 patient specimens. Our findings show that microarrays can be used for the robust and accurate diagnosis of pathogens, and further substantiate the use of microarray technology in clinical diagnostics.