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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...
Autores principales: | , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2007
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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. |
format | Text |
id | pubmed-1913542 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2007 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
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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