VIPR: A probabilistic algorithm for analysis of microbial detection microarrays |
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Authors: | Adam F Allred Guang Wu Tuya Wulan Kael F Fischer Michael R Holbrook Robert B Tesh David Wang |
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Affiliation: | (1) Departments of Molecular Microbiology and Pathology & Immunology, Washington University School of Medicine, St. Louis, Missouri, USA;(2) Department of Pathology, University of Utah School of Medicine, Salt Lake City, Utah, USA;(3) Department of Pathology, University of Texas Medical Branch, Galveston, Texas, USA;(4) NIH Integrated Research Facility, Division of Clinical Medicine, 8200 Research Plaza, Fort Detrick, Frederick, MD, 21702 |
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Abstract: |
Background All infectious disease oriented clinical diagnostic assays in use today focus on detecting the presence of a single, well defined target agent or a set of agents. In recent years, microarray-based diagnostics have been developed that greatly facilitate the highly parallel detection of multiple microbes that may be present in a given clinical specimen. While several algorithms have been described for interpretation of diagnostic microarrays, none of the existing approaches is capable of incorporating training data generated from positive control samples to improve performance. |
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