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Evaluation of the similarity of gene expression data estimated with SAGE and Affymetrix GeneChips

BACKGROUND: Serial Analysis of Gene Expression (SAGE) and microarrays have found awidespread application, but much ambiguity exists regarding the evaluation of these technologies. Cross-platform utilization of gene expression data from the SAGE and microarray technology could reduce the need for dup...

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Autores principales: van Ruissen, Fred, Ruijter, Jan M, Schaaf, Gerben J, Asgharnegad, Lida, Zwijnenburg, Danny A, Kool, Marcel, Baas, Frank
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2005
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1186021/
https://www.ncbi.nlm.nih.gov/pubmed/15955238
http://dx.doi.org/10.1186/1471-2164-6-91
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author van Ruissen, Fred
Ruijter, Jan M
Schaaf, Gerben J
Asgharnegad, Lida
Zwijnenburg, Danny A
Kool, Marcel
Baas, Frank
author_facet van Ruissen, Fred
Ruijter, Jan M
Schaaf, Gerben J
Asgharnegad, Lida
Zwijnenburg, Danny A
Kool, Marcel
Baas, Frank
author_sort van Ruissen, Fred
collection PubMed
description BACKGROUND: Serial Analysis of Gene Expression (SAGE) and microarrays have found awidespread application, but much ambiguity exists regarding the evaluation of these technologies. Cross-platform utilization of gene expression data from the SAGE and microarray technology could reduce the need for duplicate experiments and facilitate a more extensive exchange of data within the research community. This requires a measure for the correspondence of the different gene expression platforms. To date, a number of cross-platform evaluations (including a few studies using SAGE and Affymetrix GeneChips) have been conducted showing a variable, but overall low, concordance. This study evaluates these overall measures and introduces the between-ratio difference as a concordance measure pergene. RESULTS: In this study, gene expression measurements of Unigene clusters represented by both Affymetrix GeneChips HG-U133A and SAGE were compared using two independent RNA samples. After matching of the data sets the final comparison contains a small data set of 1094 unique Unigene clusters, which is unbiased with respect to expression level. Different overall correlation approaches, like Up/Down classification, contingency tables and correlation coefficients were used to compare both platforms. In addition, we introduce a novel approach to compare two platforms based on the calculation of differences between expression ratios observed in each platform for each individual transcript. This approach results in a concordance measure per gene (with statistical probability value), as opposed to the commonly used overall concordance measures between platforms. CONCLUSION: We can conclude that intra-platform correlations are generally good, but that overall agreement between the two platforms is modest. This might be due to the binomially distributed sampling variation in SAGE tag counts, SAGE annotation errors and the intensity variation between probe sets of a single gene in Affymetrix GeneChips. We cannot identify or advice which platform performs better since both have their (dis)-advantages. Therefore it is strongly recommended to perform follow-up studies of interesting genes using additional techniques. The newly introduced between-ratio difference is a filtering-independent measure for between-platform concordance. Moreover, the between-ratio difference per gene can be used to detect transcripts with similar regulation on both platforms.
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spelling pubmed-11860212005-08-16 Evaluation of the similarity of gene expression data estimated with SAGE and Affymetrix GeneChips van Ruissen, Fred Ruijter, Jan M Schaaf, Gerben J Asgharnegad, Lida Zwijnenburg, Danny A Kool, Marcel Baas, Frank BMC Genomics Methodology Article BACKGROUND: Serial Analysis of Gene Expression (SAGE) and microarrays have found awidespread application, but much ambiguity exists regarding the evaluation of these technologies. Cross-platform utilization of gene expression data from the SAGE and microarray technology could reduce the need for duplicate experiments and facilitate a more extensive exchange of data within the research community. This requires a measure for the correspondence of the different gene expression platforms. To date, a number of cross-platform evaluations (including a few studies using SAGE and Affymetrix GeneChips) have been conducted showing a variable, but overall low, concordance. This study evaluates these overall measures and introduces the between-ratio difference as a concordance measure pergene. RESULTS: In this study, gene expression measurements of Unigene clusters represented by both Affymetrix GeneChips HG-U133A and SAGE were compared using two independent RNA samples. After matching of the data sets the final comparison contains a small data set of 1094 unique Unigene clusters, which is unbiased with respect to expression level. Different overall correlation approaches, like Up/Down classification, contingency tables and correlation coefficients were used to compare both platforms. In addition, we introduce a novel approach to compare two platforms based on the calculation of differences between expression ratios observed in each platform for each individual transcript. This approach results in a concordance measure per gene (with statistical probability value), as opposed to the commonly used overall concordance measures between platforms. CONCLUSION: We can conclude that intra-platform correlations are generally good, but that overall agreement between the two platforms is modest. This might be due to the binomially distributed sampling variation in SAGE tag counts, SAGE annotation errors and the intensity variation between probe sets of a single gene in Affymetrix GeneChips. We cannot identify or advice which platform performs better since both have their (dis)-advantages. Therefore it is strongly recommended to perform follow-up studies of interesting genes using additional techniques. The newly introduced between-ratio difference is a filtering-independent measure for between-platform concordance. Moreover, the between-ratio difference per gene can be used to detect transcripts with similar regulation on both platforms. BioMed Central 2005-06-14 /pmc/articles/PMC1186021/ /pubmed/15955238 http://dx.doi.org/10.1186/1471-2164-6-91 Text en Copyright © 2005 Ruissen 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 Methodology Article
van Ruissen, Fred
Ruijter, Jan M
Schaaf, Gerben J
Asgharnegad, Lida
Zwijnenburg, Danny A
Kool, Marcel
Baas, Frank
Evaluation of the similarity of gene expression data estimated with SAGE and Affymetrix GeneChips
title Evaluation of the similarity of gene expression data estimated with SAGE and Affymetrix GeneChips
title_full Evaluation of the similarity of gene expression data estimated with SAGE and Affymetrix GeneChips
title_fullStr Evaluation of the similarity of gene expression data estimated with SAGE and Affymetrix GeneChips
title_full_unstemmed Evaluation of the similarity of gene expression data estimated with SAGE and Affymetrix GeneChips
title_short Evaluation of the similarity of gene expression data estimated with SAGE and Affymetrix GeneChips
title_sort evaluation of the similarity of gene expression data estimated with sage and affymetrix genechips
topic Methodology Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1186021/
https://www.ncbi.nlm.nih.gov/pubmed/15955238
http://dx.doi.org/10.1186/1471-2164-6-91
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