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pmid:21177656

The Gene Expression Barcode: leveraging public data repositories to begin cataloging the human and murine transcriptomes.

Matthew N McCall · Karan Uppal · Harris A Jaffee · Michael J Zilliox · Rafael A Irizarry

Nucleic acids research · 2011 doi:10.1093/nar/gkq1259

Paper

complete

Experiment

partial

Data

partial

Analysis

partial

Execution

absent

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title
The Gene Expression Barcode: leveraging public data repositories to begin cataloging the human and murine transcriptomes.
doi
10.1093/nar/gkq1259
pmid
21177656
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Matthew N McCall
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Karan Uppal
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Harris A Jaffee
[3]
Michael J Zilliox
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Rafael A Irizarry
journal
Nucleic acids research
year
2011
abstract
Various databases have harnessed the wealth of publicly available microarray data to address biological questions ranging from across-tissue differential expression to homologous gene expression. Despite their practical value, these databases rely on relative measures of expression and are unable to address the most fundamental question--which genes are expressed in a given cell type. The Gene Expression Barcode is the first database to provide reliable absolute measures of expression for most annotated genes for 131 human and 89 mouse tissue types, including diseased tissue. This is made possible by a novel algorithm that leverages information from the GEO and ArrayExpress public repositories to build statistical models that permit converting data from a single microarray into expressed/unexpressed calls for each gene. For selected platforms, users may upload data and obtain results in a matter of seconds. The raw data, curated annotation, and code used to create our resource are also available at http://rafalab.jhsph.edu/barcode.
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We achieved this by (i) developing a series of negative control experiments; (ii) leveraging information from 13 824, 18 656 and 9652 publically available chips from the Affymetrix Human Genome U133A (HGU133a), U133 Plus 2.0 (HGU133plus2) and Mouse Genome 430 2.0 (Mouse4302) platforms, respectively; and (iii) developing a novel application of the probability of expression (POE) model (10).
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We achieved this by (i) developing a series of negative control experiments; (ii) leveraging information from 13 824, 18 656 and 9652 publically available chips from the Affymetrix Human Genome U133A (HGU133a), U133 Plus 2.0 (HGU133plus2) and Mouse Genome 430 2.0 (Mouse4302) platforms, respectively; and (iii) developing a novel application of the probability of expression (POE) model (10).
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The Gene Expression Barcode is the first database to provide reliable absolute measures of expression for most annotated genes for 131 human and 89 mouse tissue types, including diseased tissue.
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This is made possible by a novel algorithm that leverages information from the GEO and ArrayExpress public repositories to build statistical models that permit converting data from a single microarray into expressed/unexpressed calls for each gene.
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