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A robust method for estimating gene expression states using Affymetrix microarray probe level data

BACKGROUND: Microarray technology is a high-throughput method for measuring the expression levels of thousand of genes simultaneously. The observed intensities combine a non-specific binding, which is a major disadvantage with microarray data. The Affymetrix GeneChip assigned a mismatch (MM) probe w...

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Autores principales: Ohtaki, Megu, Otani, Keiko, Hiyama, Keiko, Kamei, Naomi, Satoh, Kenichi, Hiyama, Eiso
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2873532/
https://www.ncbi.nlm.nih.gov/pubmed/20380745
http://dx.doi.org/10.1186/1471-2105-11-183
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author Ohtaki, Megu
Otani, Keiko
Hiyama, Keiko
Kamei, Naomi
Satoh, Kenichi
Hiyama, Eiso
author_facet Ohtaki, Megu
Otani, Keiko
Hiyama, Keiko
Kamei, Naomi
Satoh, Kenichi
Hiyama, Eiso
author_sort Ohtaki, Megu
collection PubMed
description BACKGROUND: Microarray technology is a high-throughput method for measuring the expression levels of thousand of genes simultaneously. The observed intensities combine a non-specific binding, which is a major disadvantage with microarray data. The Affymetrix GeneChip assigned a mismatch (MM) probe with the intention of measuring non-specific binding, but various opinions exist regarding usefulness of MM measures. It should be noted that not all observed intensities are associated with expressed genes and many of those are associated with unexpressed genes, of which measured values express mere noise due to non-specific binding, cross-hybridization, or stray signals. The implicit assumption that all genes are expressed leads to poor performance of microarray data analyses. We assume two functional states of a gene - expressed or unexpressed - and propose a robust method to estimate gene expression states using an order relationship between PM and MM measures. RESULTS: An indicator 'probability of a gene being expressed' was obtained using the number of probe pairs within a probe set where the PM measure exceeds the MM measure. We examined the validity of the proposed indicator using Human Genome U95 data sets provided by Affymetrix. The usefulness of 'probability of a gene being expressed' is illustrated through an exploration of candidate genes involved in neuroblastoma prognosis. We identified the candidate genes for which expression states differed (un-expressed or expressed) when compared between two outcomes. The validity of this result was subsequently confirmed by quantitative RT-PCR. CONCLUSION: The proposed qualitative evaluation, 'probability of a gene being expressed', is a useful indicator for improving microarray data analysis. It is useful to reduce the number of false discoveries. Expression states - expressed or unexpressed - correspond to the most fundamental gene function 'On' and 'Off', which can lead to biologically meaningful results.
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spelling pubmed-28735322010-05-20 A robust method for estimating gene expression states using Affymetrix microarray probe level data Ohtaki, Megu Otani, Keiko Hiyama, Keiko Kamei, Naomi Satoh, Kenichi Hiyama, Eiso BMC Bioinformatics Research article BACKGROUND: Microarray technology is a high-throughput method for measuring the expression levels of thousand of genes simultaneously. The observed intensities combine a non-specific binding, which is a major disadvantage with microarray data. The Affymetrix GeneChip assigned a mismatch (MM) probe with the intention of measuring non-specific binding, but various opinions exist regarding usefulness of MM measures. It should be noted that not all observed intensities are associated with expressed genes and many of those are associated with unexpressed genes, of which measured values express mere noise due to non-specific binding, cross-hybridization, or stray signals. The implicit assumption that all genes are expressed leads to poor performance of microarray data analyses. We assume two functional states of a gene - expressed or unexpressed - and propose a robust method to estimate gene expression states using an order relationship between PM and MM measures. RESULTS: An indicator 'probability of a gene being expressed' was obtained using the number of probe pairs within a probe set where the PM measure exceeds the MM measure. We examined the validity of the proposed indicator using Human Genome U95 data sets provided by Affymetrix. The usefulness of 'probability of a gene being expressed' is illustrated through an exploration of candidate genes involved in neuroblastoma prognosis. We identified the candidate genes for which expression states differed (un-expressed or expressed) when compared between two outcomes. The validity of this result was subsequently confirmed by quantitative RT-PCR. CONCLUSION: The proposed qualitative evaluation, 'probability of a gene being expressed', is a useful indicator for improving microarray data analysis. It is useful to reduce the number of false discoveries. Expression states - expressed or unexpressed - correspond to the most fundamental gene function 'On' and 'Off', which can lead to biologically meaningful results. BioMed Central 2010-04-12 /pmc/articles/PMC2873532/ /pubmed/20380745 http://dx.doi.org/10.1186/1471-2105-11-183 Text en Copyright ©2010 Ohtaki et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research article
Ohtaki, Megu
Otani, Keiko
Hiyama, Keiko
Kamei, Naomi
Satoh, Kenichi
Hiyama, Eiso
A robust method for estimating gene expression states using Affymetrix microarray probe level data
title A robust method for estimating gene expression states using Affymetrix microarray probe level data
title_full A robust method for estimating gene expression states using Affymetrix microarray probe level data
title_fullStr A robust method for estimating gene expression states using Affymetrix microarray probe level data
title_full_unstemmed A robust method for estimating gene expression states using Affymetrix microarray probe level data
title_short A robust method for estimating gene expression states using Affymetrix microarray probe level data
title_sort robust method for estimating gene expression states using affymetrix microarray probe level data
topic Research article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2873532/
https://www.ncbi.nlm.nih.gov/pubmed/20380745
http://dx.doi.org/10.1186/1471-2105-11-183
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