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  Distinguishing true from false positives in genomic studies: p values

Broer, L., Lill, C., Schuur, M., Amin, N., Roehr, C., Bertram, L., Ioannidis, J. P. A., & van Duijn, C. M. (2013). Distinguishing true from false positives in genomic studies: p values. European Journal of Epidemiology, 28(2), 131-138. doi:DOI 10.1007/s10654-012-9755-x.

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資料種別: 学術論文

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Broer.pdf (出版社版), 243KB
 
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Broer.pdf
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制限付き (Max Planck Institute for Molecular Genetics, MBMG; )
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著作権日付:
2013-02-01
著作権情報:
Springer Science+Business Media Dordrecht 2013
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 作成者:
Broer, L., 著者
Lill, C.1, 著者           
Schuur, M., 著者
Amin, N., 著者
Roehr, C.2, 著者           
Bertram, L.1, 著者           
Ioannidis, J. P. A., 著者
van Duijn, C. M., 著者
所属:
1Neuropsychiatric Genetics (Lars Bertram), Dept. of Vertebrate Genomics (Head: Hans Lehrach), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_1479655              
2Cancer Genomics (Michal-Ruth Schweiger), Dept. of Vertebrate Genomics (Head: Hans Lehrach), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_1479649              

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キーワード: venice criteria significance thresholds "-omics" alzheimer's disease genetic association alzheimer-disease metaanalyses probability trials
 要旨: Distinguishing true from false positive findings is a major challenge in human genetic epidemiology. Several strategies have been devised to facilitate this, including the positive predictive value (PPV) and a set of epidemiological criteria, known as the "Venice" criteria. The PPV measures the probability of a true association, given a statistically significant finding, while the Venice criteria grade the credibility based on the amount of evidence, consistency of replication and protection from bias. A vast majority of journals use significance thresholds to identify the true positive findings. We studied the effect of p value thresholds on the PPV and used the PPV and Venice criteria to define usable thresholds of statistical significance. Theoretical and empirical analyses of data published on AlzGene show that at a nominal p value threshold of 0.05 most "positive" findings will turn out to be false if the prior probability of association is below 0.10 even if the statistical power of the study is higher than 0.80. However, in underpowered studies (0.25) with a low prior probability of 1 x 10(-3), a p value of 1 x 10(-5) yields a high PPV (> 96 %). Here we have shown that the p value threshold of 1 x 10(-5) gives a very strong evidence of association in almost all studies. However, in the case of a very high prior probability of association (0.50) a p value threshold of 0.05 may be sufficient, while for studies with very low prior probability of association (1 x 10(-4); genome-wide association studies for instance) 1 x 10(-7) may serve as a useful threshold to declare significance.

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言語: eng - English
 日付: 2012-05-012012-12-112013-02-012013
 出版の状態: 出版
 ページ: -
 出版情報: -
 目次: -
 査読: -
 識別子(DOI, ISBNなど): その他: WOS:000316638900003
DOI: DOI 10.1007/s10654-012-9755-x
ISSN: 0393-2990
URI: ://WOS:000316638900003http://download.springer.com/static/pdf/847/art%253A10.1007%252Fs10654-012-9755-x.pdf?auth66=1396692323_ccd10c7080a3959d3922a603e4b65594&ext=.pdf
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出版物 1

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出版物名: European Journal of Epidemiology
  省略形 : Eur J Epidemiol
種別: 学術雑誌
 著者・編者:
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出版社, 出版地: Dordrecht : Springer
ページ: - 巻号: 28 (2) 通巻号: - 開始・終了ページ: 131 - 138 識別子(ISBN, ISSN, DOIなど): -