About: Nonparametric methods for the analysis of single-color pathogen microarrays

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An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Nonparametric methods for the analysis of single-color pathogen microarrays
Creator	Palacios, Gustavo Briese, Thomas Conlan, Sean Hui, Jeffrey Quan, Phenix-Lan Lipkin, Ian Hornig, Mady Jabado, Omar
Source	Medline; PMC
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.
has issue date	2010-06-28(xsd:dateTime)
bibo:doi	10.1186/1471-2105-11-354
bibo:pmid	20584331
has license	cc-by
sha1sum (hex)	448c6dce11a897a8baa0815f46a77307b16049db
schema:url	https://doi.org/10.1186/1471-2105-11-354
resource representing a document's title	Nonparametric methods for the analysis of single-color pathogen microarrays
has PubMed Central identifier	PMC2909221
has PubMed identifier	20584331
schema:publication	BMC Bioinformatics
resource representing a document's body	covid:448c6dce11a897a8baa0815f46a77307b16049db#body_text
is schema:about of	named entity 'oligonucleotide' covid:arg/448c6dce11a897a8baa0815f46a77307b16049db named entity 'DEVIATIONS' named entity 'NUCLEIC ACID' named entity 'TARGET' named entity 'TASK' named entity 'REVEALED' named entity 'CLINICAL' named entity 'APPLIED' named entity 'ANALYSIS' named entity 'DISTRIBUTION' named entity 'EFFECT' named entity 'SIGNAL' named entity 'APPROACHES' named entity 'COMPOSITION' named entity 'COLOR' named entity 'NORMALITY' named entity 'TEMPLATE' named entity 'PROFOUND' named entity 'SAMPLES' named entity 'OLIGONUCLEOTIDE MICROARRAY' named entity 'PATHOGEN' named entity 'SINGLE' named entity 'ANALYSIS' named entity 'METHODS' named entity 'PATHOGEN SURVEILLANCE' named entity 'IS A' named entity 'BACKGROUND' named entity 'CONCENTRATION' named entity 'DISCOVERY' named entity 'INTEGRITY' named entity 'HOST' named entity 'MICROARRAY DATA' named entity 'FREE' named entity 'FLUORESCENT' named entity 'MICROARRAYS' named entity 'HAVE' named entity 'microarray' named entity 'integrity' named entity 'Exploratory analysis' named entity 'nucleic acid' named entity 'microarrays' named entity 'microarray' named entity 'hybridization' named entity 'variance' named entity 'minus strand' named entity 'genome' named entity 'probability' named entity 'statistical computing' named entity 'genus' named entity 'database' named entity 'semi-supervised' named entity 'false-positive result' named entity 'probability' named entity 'Hybridization' named entity 'microarray' named entity 'RNA' named entity 'central tendency' named entity 'viruses' named entity 'viruses' named entity 'null hypotheses' named entity 'antisense' named entity 'viruses' named entity 'influenza virus' named entity 'parame' named entity '95%' named entity 'false positive' named entity 'microarray' named entity 'nasal lavage' named entity 'dendrimer' named entity 'randomly distributed' named entity 'negative control' named entity 'multiple sequence alignment' named entity 'nonparametric'

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