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Tissue Expression contains human tissue and cell-type specific gene expression data
from BioGPS [1] (until recently from the Novartis GNF SymAtlas database [2]). This data
was generated on Affymetrix microarrays (HGU133A and a custom array). We present a
subset of the tissues and cell types from the BioGPS dataset that are most relevant
for T1D research.
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Operating Instructions:
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To operate the program, you specify one or more genes
and click the "Submit Query" button. You can
specify genes by entering identifiers in the text box, uploading a file of
gene identifiers, or choosing an existing gene list from the drop-down
menu. The most
reliable gene identifiers are Entrez Gene IDs (e.g., 3630). See Entering Gene Identifiers for more information.
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Results page:
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The results page displays a gray-scale heatmap of the specified genes.
If a gene identifier matches multiple genes, a box will be displayed on the results page saying "There were ambiguous terms in your query. Click here to resolve them." You can click the link to correct the identifier. To pick the correct identifier(s), click on the box next to the appropriate identifier(s) and click on Submit Corrections. A new results page with the correct identifier(s) will be shown.
You can add a gene to the results by typing a gene identifier in the "Add a new
gene box" and clicking Go.
You can save the displayed genes by clicking the "save list to My T1DBase" link
at the top of the page. You can use the genes in another T1DBase program by clicking
the "send list to tool" link at the top of the page. Clicking on one of the tools
will cause a new page to be loaded with the gene list already included in the "Select a T1DBase List".
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Scientific details:
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Signal intensity values were converted to ranks within the experiments.
For genes represented by more than one probeset, we averaged the intensity
signals for each probeset across all tissues and chose the probeset with the highest
average value. The rank transformation of the expression values enables
comparison of gene expression across different organisms and tissues.
References:
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Wu C, Orozco C, Boyer J, Leglise M, Goodale J, Batalov S, Hodge CL, Haase J, Janes J, Huss JW 3rd, Su AI. (2010) BioGPS: an extensible and customizable portal for querying and organizing gene annotation resources. Genome Biol. 2009 10(11):R130
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Su AI, Wiltshire T, Batalov S, Lapp H, Ching KA, Block D, Zhang J, Soden R, Hayakawa M, Kreiman G, Cooke MP, Walker JR, Hogenesch JB (2004) A gene atlas of the mouse and human protein-encoding transcriptomes. Proc Natl Acad Sci U S A. 2004 Apr 20;101(16):6062-7
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