Statistically designing microarrays and microarray experiments to enhance sensitivity and specificity.

2.50
Hdl Handle:
http://hdl.handle.net/2336/75753
Title:
Statistically designing microarrays and microarray experiments to enhance sensitivity and specificity.
Authors:
Hsu, Jason C; Chang, Jane; Wang, Tao; Steingrimsson, Eirikur; Magnusson, Magnus Karl; Bergsteinsdottir, Kristin
Citation:
Brief. Bioinformatics. 2007, 8(1):22-31
Issue Date:
1-Jan-2007
Abstract:
Gene expression signatures from microarray experiments promise to provide important prognostic tools for predicting disease outcome or response to treatment. A number of microarray studies in various cancers have reported such gene signatures. However, the overlap of gene signatures in the same disease has been limited so far, and some reported signatures have not been reproduced in other populations. Clearly, the methods used for verifying novel gene signatures need improvement. In this article, we describe an experiment in which microarrays and sample hybridization are designed according to the statistical principles of randomization, replication and blocking. Our results show that such designs provide unbiased estimation of differential expression levels as well as powerful tests for them.
Description:
To access publisher full text version of this article. Please click on the hyperlink in Additional Links field
Additional Links:
http://dx.doi.org/10.1093/bib/bbl023

Full metadata record

DC FieldValue Language
dc.contributor.authorHsu, Jason C-
dc.contributor.authorChang, Jane-
dc.contributor.authorWang, Tao-
dc.contributor.authorSteingrimsson, Eirikur-
dc.contributor.authorMagnusson, Magnus Karl-
dc.contributor.authorBergsteinsdottir, Kristin-
dc.date.accessioned2009-07-28T11:06:18Z-
dc.date.available2009-07-28T11:06:18Z-
dc.date.issued2007-01-01-
dc.date.submitted2009-07-28-
dc.identifier.citationBrief. Bioinformatics. 2007, 8(1):22-31en
dc.identifier.issn1467-5463-
dc.identifier.pmid16899493-
dc.identifier.doi10.1093/bib/bbl023-
dc.identifier.urihttp://hdl.handle.net/2336/75753-
dc.descriptionTo access publisher full text version of this article. Please click on the hyperlink in Additional Links fielden
dc.description.abstractGene expression signatures from microarray experiments promise to provide important prognostic tools for predicting disease outcome or response to treatment. A number of microarray studies in various cancers have reported such gene signatures. However, the overlap of gene signatures in the same disease has been limited so far, and some reported signatures have not been reproduced in other populations. Clearly, the methods used for verifying novel gene signatures need improvement. In this article, we describe an experiment in which microarrays and sample hybridization are designed according to the statistical principles of randomization, replication and blocking. Our results show that such designs provide unbiased estimation of differential expression levels as well as powerful tests for them.en
dc.language.isoenen
dc.publisherH. Stewart Publicationsen
dc.relation.urlhttp://dx.doi.org/10.1093/bib/bbl023en
dc.subject.meshBreast Neoplasmsen
dc.subject.meshFemaleen
dc.subject.meshGene Expression Profilingen
dc.subject.meshHumansen
dc.subject.meshMiddle Ageden
dc.subject.meshModels, Statisticalen
dc.subject.meshOligonucleotide Array Sequence Analysisen
dc.subject.meshRandom Allocationen
dc.subject.meshReproducibility of Resultsen
dc.subject.meshResearch Designen
dc.subject.meshSensitivity and Specificityen
dc.titleStatistically designing microarrays and microarray experiments to enhance sensitivity and specificity.en
dc.typeArticleen
dc.contributor.departmentDepartment of Statistics, The Ohio State University, 1958 Neil Avenue Columbus, Ohio 43210, USA. Hsu.1@osu.eduen
dc.identifier.journalBriefings in bioinformaticsen
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