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Probabilistic estimation of microarray data reliability and underlying gene expression

BACKGROUND: The availability of high throughput methods for measurement of mRNA concentrations makes the reliability of conclusions drawn from the data and global quality control of samples and hybridization important issues. We address these issues by an information theoretic approach, applied to d...

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Autores principales: Bilke, Sven, Breslin, Thomas, Sigvardsson, Mikael
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2003
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC222958/
https://www.ncbi.nlm.nih.gov/pubmed/12967349
http://dx.doi.org/10.1186/1471-2105-4-40
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author Bilke, Sven
Breslin, Thomas
Sigvardsson, Mikael
author_facet Bilke, Sven
Breslin, Thomas
Sigvardsson, Mikael
author_sort Bilke, Sven
collection PubMed
description BACKGROUND: The availability of high throughput methods for measurement of mRNA concentrations makes the reliability of conclusions drawn from the data and global quality control of samples and hybridization important issues. We address these issues by an information theoretic approach, applied to discretized expression values in replicated gene expression data. RESULTS: Our approach yields a quantitative measure of two important parameter classes: First, the probability P(σ|S) that a gene is in the biological state σ in a certain variety, given its observed expression S in the samples of that variety. Second, sample specific error probabilities which serve as consistency indicators of the measured samples of each variety. The method and its limitations are tested on gene expression data for developing murine B-cells and a t-test is used as reference. On a set of known genes it performs better than the t-test despite the crude discretization into only two expression levels. The consistency indicators, i.e. the error probabilities, correlate well with variations in the biological material and thus prove efficient. CONCLUSIONS: The proposed method is effective in determining differential gene expression and sample reliability in replicated microarray data. Already at two discrete expression levels in each sample, it gives a good explanation of the data and is comparable to standard techniques.
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spelling pubmed-2229582003-10-24 Probabilistic estimation of microarray data reliability and underlying gene expression Bilke, Sven Breslin, Thomas Sigvardsson, Mikael BMC Bioinformatics Methodology Article BACKGROUND: The availability of high throughput methods for measurement of mRNA concentrations makes the reliability of conclusions drawn from the data and global quality control of samples and hybridization important issues. We address these issues by an information theoretic approach, applied to discretized expression values in replicated gene expression data. RESULTS: Our approach yields a quantitative measure of two important parameter classes: First, the probability P(σ|S) that a gene is in the biological state σ in a certain variety, given its observed expression S in the samples of that variety. Second, sample specific error probabilities which serve as consistency indicators of the measured samples of each variety. The method and its limitations are tested on gene expression data for developing murine B-cells and a t-test is used as reference. On a set of known genes it performs better than the t-test despite the crude discretization into only two expression levels. The consistency indicators, i.e. the error probabilities, correlate well with variations in the biological material and thus prove efficient. CONCLUSIONS: The proposed method is effective in determining differential gene expression and sample reliability in replicated microarray data. Already at two discrete expression levels in each sample, it gives a good explanation of the data and is comparable to standard techniques. BioMed Central 2003-09-10 /pmc/articles/PMC222958/ /pubmed/12967349 http://dx.doi.org/10.1186/1471-2105-4-40 Text en Copyright © 2003 Bilke et al; licensee BioMed Central Ltd. This is an Open Access article: verbatim copying and redistribution of this article are permitted in all media for any purpose, provided this notice is preserved along with the article's original URL.
spellingShingle Methodology Article
Bilke, Sven
Breslin, Thomas
Sigvardsson, Mikael
Probabilistic estimation of microarray data reliability and underlying gene expression
title Probabilistic estimation of microarray data reliability and underlying gene expression
title_full Probabilistic estimation of microarray data reliability and underlying gene expression
title_fullStr Probabilistic estimation of microarray data reliability and underlying gene expression
title_full_unstemmed Probabilistic estimation of microarray data reliability and underlying gene expression
title_short Probabilistic estimation of microarray data reliability and underlying gene expression
title_sort probabilistic estimation of microarray data reliability and underlying gene expression
topic Methodology Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC222958/
https://www.ncbi.nlm.nih.gov/pubmed/12967349
http://dx.doi.org/10.1186/1471-2105-4-40
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AT sigvardssonmikael probabilisticestimationofmicroarraydatareliabilityandunderlyinggeneexpression