title: Robust methods for accurate diagnosis using pan-microbiological oligonucleotide microarrays.
abstract: BACKGROUND
  To address the limitations of traditional virus and pathogen detection methodologies in clinical diagnosis, scientists have developed high-throughput oligonucleotide microarrays to rapidly identify infectious agents. However, objectively identifying pathogens from the complex hybridization patterns of these massively multiplexed arrays remains challenging.
  
  
  METHODS
  In this study, we conceived an automated method based on the hypergeometric distribution for identifying pathogens in multiplexed arrays and compared it to five other methods. We evaluated these metrics: 1) accurate prediction, whether the top ranked prediction(s) match the real virus(es); 2) four accuracy scores.
  
  
  RESULTS
  Though accurate prediction and high specificity and sensitivity can be achieved with several methods, the method based on hypergeometric distribution provides a significant advantage in term of positive predicting value with two to sixty folds the positive predicting values of other methods.
  
  
  CONCLUSIONS
  The proposed multi-specie array analysis based on the hypergeometric distribution addresses shortcomings of previous methods by enhancing signals of positively hybridized probes.
authors.affiliation: Center for Biomedical Informatics and Section of Genetic Medicine, Dept, of Medicine, The University of Chicago, Chicago, 5841 South Maryland Ave, Ill, USA. yuwang_la@yahoo.com
authors.forename: Yang
authors.initials: Y
authors.lastname: Liu
authors.forename: Lee
authors.initials: L
authors.lastname: Sam
authors.forename: Jianrong
authors.initials: J
authors.lastname: Li
authors.forename: Yves A
authors.initials: YA
authors.lastname: Lussier
mesh_terms: D001424:Bacterial Infections / Q000175:diagnosis; D019295:Computational Biology / Q000379:methods; D007239:Infections / Q000175:diagnosis*; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D010272:Parasitic Diseases / Q000175:diagnosis; D012680:Sensitivity and Specificity; D014777:Virus Diseases / Q000175:diagnosis