Project description:Background: The analysis of oligonucleotide microarray data in pathogen surveillance and discovery assays 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: An examination of both positive predictive value and false positive rates was employed 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, it was the chi-square that 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. A set of comprehensive probes covering vertebrate viruses was designed and printed using Agilent in-situ fabrication. Cells in tissue culture were infected with various viruses, then RNA was harvested. RNA was converted to cDNA, then amplified, labeled and hybridized to the array.
Project description:Background: The analysis of oligonucleotide microarray data in pathogen surveillance and discovery assays 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: An examination of both positive predictive value and false positive rates was employed 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, it was the chi-square that 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.
Project description:Background: The analysis of oligonucleotide microarray data in pathogen surveillance and discovery assays 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: An examination of both positive predictive value and false positive rates was employed 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, it was the chi-square that 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. A set of comprehensive probes covering vertebrate viruses was designed and printed using Agilent in-situ fabrication. Cells in tissue culture were infected with West Nile Virus, then RNA was harvested. RNA was converted to cDNA, then copy number was quantified by quantatative real-time PCR. RNA stocks were diluted to 10^4 or 10^6 copies per microliter then converted to cDNA, amplified, labeled and hybridized to the array. Human Lung RNA was used as a control and spiked in at 10ng or 200ng.
Project description:Data from the IAH/VLA diagnostic pathogen/virus detection microarray. The array platform for this data is GEO accession GPL5725 (provisional), and consists of 5824 oligos representing over 100 viral families, species and subtypes. The data set itself consists of 12 arrays, 4 hybridised with RNA from cell cultured foot-and-mouth disease virus (FMDV) type O, 3 hybridised with RNA from FMDV type A, 1 hybridised with RNA from a sheep infected with FMDV type O, and 4 hybridised with cell-cultured Avian Infectious Bronchitis virus (IBV). Keywords: Virus Detection Microarray
Project description:Background: The analysis of oligonucleotide microarray data in pathogen surveillance and discovery assays 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: An examination of both positive predictive value and false positive rates was employed 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, it was the chi-square that 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.