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  Microarray Based Diagnosis Profits from Better Documentation of Gene Expression Signatures

Kostka, D., & Spang, R. (2008). Microarray Based Diagnosis Profits from Better Documentation of Gene Expression Signatures. PLoS Computational Biology, 4(2), e22-e22. doi:10.1371/journal.pcbi.0040022.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0010-805E-C Version Permalink: http://hdl.handle.net/11858/00-001M-0000-0010-805F-A
Genre: Journal Article
Alternative Title : PLoS Comput Biol

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journal.pcbi.0040022.pdf (Any fulltext), 108KB
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 Creators:
Kostka, Dennis1, Author
Spang, Rainer2, Author              
Affiliations:
1Max Planck Society, ou_persistent13              
2Dept. of Computational Molecular Biology (Head: Martin Vingron), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_1433547              

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 Abstract: Microarray gene expression signatures hold great promise to improve diagnosis and prognosis of disease. However, current documentation standards of such signatures do not allow for an unambiguous application to study-external patients. This hinders independent evaluation, effectively delaying the use of signatures in clinical practice. Data from eight publicly available clinical microarray studies were analyzed and the consistency of study-internal with study-external diagnoses was evaluated. Study-external classifications were based on documented information only. Documenting a signature is conceptually different from reporting a list of genes. We show that even the exact quantitative specification of a classification rule alone does not define a signature unambiguously. We found that discrepancy between study-internal and study-external diagnoses can be as frequent as 30% (worst case) and 18% (median). By using the proposed documentation by value strategy, which documents quantitative preprocessing information, the median discrepancy was reduced to 1%. The process of evaluating microarray gene expression diagnostic signatures and bringing them to clinical practice can be substantially improved and made more reliable by better documentation of the signatures.

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Language(s): eng - English
 Dates: 2008-02-15
 Publication Status: Published in print
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Title: PLoS Computational Biology
  Alternative Title : PLoS Comput Biol
Source Genre: Journal
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Pages: - Volume / Issue: 4 (2) Sequence Number: - Start / End Page: e22 - e22 Identifier: ISSN: 1553-7358