Use of signal thresholds to determine significant changes in microarray data analyses

Detalhes bibliográficos
Autor(a) principal: Xinmin,Li
Data de Publicação: 2005
Outros Autores: Kim,Jaejung, Zhou,Jian, Gu,Weikuan, Quigg,Richard
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Genetics and Molecular Biology
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572005000200002
Resumo: The use of a constant fold-change to determine significant changes in gene expression has been widely accepted for its intuition and ease of use in microarray data analysis, but this concept has been increasingly criticized because it does not reflect signal intensity and can result in a substantial number of false positives and false negatives. To resolve this dilemma, we have analyzed 65 replicate Affymetrix chip-chip comparisons and determined a series of user adjustable signal-dependent thresholds which do not require replicates and offer a 95% confidence interval. Quantitative RT-PCR shows that such thresholds significantly improve the power to discriminate biological changes in mRNA from noise and reduce false calls compared to the traditional two-fold threshold. The user-friendly nature of this approach means that it can be easily applied by any user of microarray analysis, even those without any specialized knowledge of computational techniques or statistics. Noise is a function of signal intensity not only for Affymetrix data but also for cDNA array data, analysis of which may also be benefited by our methodology.
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spelling Use of signal thresholds to determine significant changes in microarray data analysesmicroarraysignal thresholdaffymetrixdata analysisThe use of a constant fold-change to determine significant changes in gene expression has been widely accepted for its intuition and ease of use in microarray data analysis, but this concept has been increasingly criticized because it does not reflect signal intensity and can result in a substantial number of false positives and false negatives. To resolve this dilemma, we have analyzed 65 replicate Affymetrix chip-chip comparisons and determined a series of user adjustable signal-dependent thresholds which do not require replicates and offer a 95% confidence interval. Quantitative RT-PCR shows that such thresholds significantly improve the power to discriminate biological changes in mRNA from noise and reduce false calls compared to the traditional two-fold threshold. The user-friendly nature of this approach means that it can be easily applied by any user of microarray analysis, even those without any specialized knowledge of computational techniques or statistics. Noise is a function of signal intensity not only for Affymetrix data but also for cDNA array data, analysis of which may also be benefited by our methodology.Sociedade Brasileira de Genética2005-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572005000200002Genetics and Molecular Biology v.28 n.2 2005reponame:Genetics and Molecular Biologyinstname:Sociedade Brasileira de Genética (SBG)instacron:SBG10.1590/S1415-47572005000200002info:eu-repo/semantics/openAccessXinmin,LiKim,JaejungZhou,JianGu,WeikuanQuigg,Richardeng2005-07-11T00:00:00Zoai:scielo:S1415-47572005000200002Revistahttp://www.gmb.org.br/ONGhttps://old.scielo.br/oai/scielo-oai.php||editor@gmb.org.br1678-46851415-4757opendoar:2005-07-11T00:00Genetics and Molecular Biology - Sociedade Brasileira de Genética (SBG)false
dc.title.none.fl_str_mv Use of signal thresholds to determine significant changes in microarray data analyses
title Use of signal thresholds to determine significant changes in microarray data analyses
spellingShingle Use of signal thresholds to determine significant changes in microarray data analyses
Xinmin,Li
microarray
signal threshold
affymetrix
data analysis
title_short Use of signal thresholds to determine significant changes in microarray data analyses
title_full Use of signal thresholds to determine significant changes in microarray data analyses
title_fullStr Use of signal thresholds to determine significant changes in microarray data analyses
title_full_unstemmed Use of signal thresholds to determine significant changes in microarray data analyses
title_sort Use of signal thresholds to determine significant changes in microarray data analyses
author Xinmin,Li
author_facet Xinmin,Li
Kim,Jaejung
Zhou,Jian
Gu,Weikuan
Quigg,Richard
author_role author
author2 Kim,Jaejung
Zhou,Jian
Gu,Weikuan
Quigg,Richard
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Xinmin,Li
Kim,Jaejung
Zhou,Jian
Gu,Weikuan
Quigg,Richard
dc.subject.por.fl_str_mv microarray
signal threshold
affymetrix
data analysis
topic microarray
signal threshold
affymetrix
data analysis
description The use of a constant fold-change to determine significant changes in gene expression has been widely accepted for its intuition and ease of use in microarray data analysis, but this concept has been increasingly criticized because it does not reflect signal intensity and can result in a substantial number of false positives and false negatives. To resolve this dilemma, we have analyzed 65 replicate Affymetrix chip-chip comparisons and determined a series of user adjustable signal-dependent thresholds which do not require replicates and offer a 95% confidence interval. Quantitative RT-PCR shows that such thresholds significantly improve the power to discriminate biological changes in mRNA from noise and reduce false calls compared to the traditional two-fold threshold. The user-friendly nature of this approach means that it can be easily applied by any user of microarray analysis, even those without any specialized knowledge of computational techniques or statistics. Noise is a function of signal intensity not only for Affymetrix data but also for cDNA array data, analysis of which may also be benefited by our methodology.
publishDate 2005
dc.date.none.fl_str_mv 2005-01-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572005000200002
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572005000200002
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/S1415-47572005000200002
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Sociedade Brasileira de Genética
publisher.none.fl_str_mv Sociedade Brasileira de Genética
dc.source.none.fl_str_mv Genetics and Molecular Biology v.28 n.2 2005
reponame:Genetics and Molecular Biology
instname:Sociedade Brasileira de Genética (SBG)
instacron:SBG
instname_str Sociedade Brasileira de Genética (SBG)
instacron_str SBG
institution SBG
reponame_str Genetics and Molecular Biology
collection Genetics and Molecular Biology
repository.name.fl_str_mv Genetics and Molecular Biology - Sociedade Brasileira de Genética (SBG)
repository.mail.fl_str_mv ||editor@gmb.org.br
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