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Nucleic Acids Research Advance Access published online on September 29, 2006

Nucleic Acids Research, doi:10.1093/nar/gkl565
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Published by Oxford University Press 2006

Computational Biology

Automated identification of multiple micro-organisms from resequencing DNA microarrays

Anthony P. Malanoski*, Baochuan Lin, Zheng Wang, Joel M. Schnur and David A. Stenger

Center for Bio/Molecular Science and Engineering, Code 6900, Naval Research Laboratory Washington DC 20375, USA

*To whom correspondence should be addressed. Tel: +1 202 404 5432; Fax: +1 202 767 9594; Email: anthony.malanoski{at}nrl.navy.mil

Received May 9, 2006. Revised July 18, 2006. Accepted July 19, 2006.

There is an increasing recognition that detailed nucleic acid sequence information will be useful and even required in the diagnosis, treatment and surveillance of many significant pathogens. Because generating detailed information about pathogens leads to significantly larger amounts of data, it is necessary to develop automated analysis methods to reduce analysis time and to standardize identification criteria. This is especially important for multiple pathogen assays designed to reduce assay time and costs. In this paper, we present a successful algorithm for detecting pathogens and reporting the maximum level of detail possible using multi-pathogen resequencing microarrays. The algorithm filters the sequence of base calls from the microarray and finds entries in genetic databases that most closely match. Taxonomic databases are then used to relate these entries to each other so that the microorganism can be identified. Although developed using a resequencing microarray, the approach is applicable to any assay method that produces base call sequence information. The success and continued development of this approach means that a non-expert can now perform unassisted analysis of the results obtained from partial sequence data.


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