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PMID: 17559689 Published · epublish English Journal Article Research Support, Non-U.S. Gov't

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

BMC bioinformatics ·Vol. 8 ·2007-06-11 ·Pages 194

Yu H, Wang F, Tu K, Xie L, Li YY, Li YX

Abstract

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. 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. 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.

MeSH Terms
Algorithms Base Sequence DNA Probes/genetics Databases, Genetic Gene Expression Profiling/methods Information Storage and Retrieval Molecular Sequence Data Oligonucleotide Array Sequence Analysis/methods Sequence Alignment/methods Sequence Analysis, DNA/methods Transcription Factors/genetics
Chemicals
DNA Probes Transcription Factors
Authors & Affiliations
6 authors, click to expand affiliations / ORCID
Yu Hui
Shanghai Center for Bioinformation Technology, Shanghai, PR China. [email protected] <[email protected]>
Wang Feng
Tu Kang
Xie Lu
Li Yuan-Yuan
Li Yi-Xue
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Article Info
Journal
BMC bioinformatics
Abbr.
BMC Bioinformatics
ISSN
1471-2105
Published
2007-06-11
Epub
2007-00-11
Pages
194
Language
English
Region
England
NLM ID
100965194
PMCID
PMC1913542
Subset
IM
Analysis Services
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