Ontology highlight
ABSTRACT: Background
The analysis of oligonucleotide microarray data in pathogen surveillance and discovery is a challenging task. Target template concentration, nucleic acid integrity, and host nucleic acid composition can each have a profound effect on signal distribution. Exploratory analysis of fluorescent signal distribution in clinical samples has revealed deviations from normality, suggesting that distribution-free approaches should be applied.Results
Positive predictive value and false positive rates were examined to assess the utility of three well-established nonparametric methods for the analysis of viral array hybridization data: (1) Mann-Whitney U, (2) the Spearman correlation coefficient and (3) the chi-square test. Of the three tests, the chi-square proved most useful.Conclusions
The acceptance of microarray use for routine clinical diagnostics will require that the technology be accompanied by simple yet reliable analytic methods. We report that our implementation of the chi-square test yielded a combination of low false positive rates and a high degree of predictive accuracy.
SUBMITTER: Jabado OJ
PROVIDER: S-EPMC2909221 | biostudies-literature | 2010 Jun
REPOSITORIES: biostudies-literature
Jabado Omar J OJ Conlan Sean S Quan Phenix-Lan PL Hui Jeffrey J Palacios Gustavo G Hornig Mady M Briese Thomas T Lipkin W Ian WI
BMC bioinformatics 20100628
<h4>Background</h4>The analysis of oligonucleotide microarray data in pathogen surveillance and discovery is a challenging task. Target template concentration, nucleic acid integrity, and host nucleic acid composition can each have a profound effect on signal distribution. Exploratory analysis of fluorescent signal distribution in clinical samples has revealed deviations from normality, suggesting that distribution-free approaches should be applied.<h4>Results</h4>Positive predictive value and f ...[more]