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Nonparametric methods for the analysis of single-color pathogen microarrays.


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

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Nonparametric methods for the analysis of single-color pathogen microarrays.

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]

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