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

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About: Transcript-level annotation of Affymetrix probesets improves the interpretation of gene expression data Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Transcript-level annotation of Affymetrix probesets improves the interpretation of gene expression data
Creator	Li, Yi-Xue Li, Yuan-Yuan Yu, Hui Tu, Kang Xie, Lu
Source	PMC
abstract	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.
has issue date	2007-06-11(xsd:dateTime)
bibo:doi	10.1186/1471-2105-8-194
bibo:pmid	17559689
has license	cc-by
sha1sum (hex)	2bf62ecb50fd95973de0bf6c1285ac3475fc4cc8
schema:url	https://doi.org/10.1186/1471-2105-8-194
resource representing a document's title	Transcript-level annotation of Affymetrix probesets improves the interpretation of gene expression data
has PubMed Central identifier	PMC1913542
has PubMed identifier	17559689
schema:publication	BMC Bioinformatics
resource representing a document's body	covid:2bf62ecb50fd95973de0bf6c1285ac3475fc4cc8#body_text
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