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Transcript-level annotation of Affymetrix probesets improves the interpretation of gene expression data

BACKGROUND: The wide use of Affymetrix microarray in broadened fields of biological research has made the probeset annotation an important issue. Standard Affymetrix probeset annotation is at gene level, i.e. a probeset is precisely linked to a gene, and probeset intensity is interpreted as gene exp...

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Autores principales: Yu, Hui, Wang, Feng, Tu, Kang, Xie, Lu, Li, Yuan-Yuan, Li, Yi-Xue
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2007
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1913542/
https://www.ncbi.nlm.nih.gov/pubmed/17559689
http://dx.doi.org/10.1186/1471-2105-8-194
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author Yu, Hui
Wang, Feng
Tu, Kang
Xie, Lu
Li, Yuan-Yuan
Li, Yi-Xue
author_facet Yu, Hui
Wang, Feng
Tu, Kang
Xie, Lu
Li, Yuan-Yuan
Li, Yi-Xue
author_sort Yu, Hui
collection PubMed
description BACKGROUND: The wide use of Affymetrix microarray in broadened fields of biological research has made the probeset annotation an important issue. Standard Affymetrix probeset annotation is at gene level, i.e. a probeset is precisely linked to a gene, and probeset intensity is interpreted as gene expression. The increased knowledge that one gene may have multiple transcript variants clearly brings up the necessity of updating this gene-level annotation to a refined transcript-level. RESULTS: Through performing rigorous alignments of the Affymetrix probe sequences against a comprehensive pool of currently available transcript sequences, and further linking the probesets to the International Protein Index, we generated transcript-level or protein-level annotation tables for two popular Affymetrix expression arrays, Mouse Genome 430A 2.0 Array and Human Genome U133A Array. Application of our new annotations in re-examining existing expression data sets shows increased expression consistency among synonymous probesets and strengthened expression correlation between interacting proteins. CONCLUSION: By refining the standard Affymetrix annotation of microarray probesets from the gene level to the transcript level and protein level, one can achieve a more reliable interpretation of their experimental data, which may lead to discovery of more profound regulatory mechanism.
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spelling pubmed-19135422007-07-10 Transcript-level annotation of Affymetrix probesets improves the interpretation of gene expression data Yu, Hui Wang, Feng Tu, Kang Xie, Lu Li, Yuan-Yuan Li, Yi-Xue BMC Bioinformatics Research Article BACKGROUND: The wide use of Affymetrix microarray in broadened fields of biological research has made the probeset annotation an important issue. Standard Affymetrix probeset annotation is at gene level, i.e. a probeset is precisely linked to a gene, and probeset intensity is interpreted as gene expression. The increased knowledge that one gene may have multiple transcript variants clearly brings up the necessity of updating this gene-level annotation to a refined transcript-level. RESULTS: Through performing rigorous alignments of the Affymetrix probe sequences against a comprehensive pool of currently available transcript sequences, and further linking the probesets to the International Protein Index, we generated transcript-level or protein-level annotation tables for two popular Affymetrix expression arrays, Mouse Genome 430A 2.0 Array and Human Genome U133A Array. Application of our new annotations in re-examining existing expression data sets shows increased expression consistency among synonymous probesets and strengthened expression correlation between interacting proteins. CONCLUSION: By refining the standard Affymetrix annotation of microarray probesets from the gene level to the transcript level and protein level, one can achieve a more reliable interpretation of their experimental data, which may lead to discovery of more profound regulatory mechanism. BioMed Central 2007-06-11 /pmc/articles/PMC1913542/ /pubmed/17559689 http://dx.doi.org/10.1186/1471-2105-8-194 Text en Copyright © 2007 Yu 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
Yu, Hui
Wang, Feng
Tu, Kang
Xie, Lu
Li, Yuan-Yuan
Li, Yi-Xue
Transcript-level annotation of Affymetrix probesets improves the interpretation of gene expression data
title Transcript-level annotation of Affymetrix probesets improves the interpretation of gene expression data
title_full Transcript-level annotation of Affymetrix probesets improves the interpretation of gene expression data
title_fullStr Transcript-level annotation of Affymetrix probesets improves the interpretation of gene expression data
title_full_unstemmed Transcript-level annotation of Affymetrix probesets improves the interpretation of gene expression data
title_short Transcript-level annotation of Affymetrix probesets improves the interpretation of gene expression data
title_sort transcript-level annotation of affymetrix probesets improves the interpretation of gene expression data
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1913542/
https://www.ncbi.nlm.nih.gov/pubmed/17559689
http://dx.doi.org/10.1186/1471-2105-8-194
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