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Reporting Correct p Values in VEGAS Analyses

  • Julian Hecker (a1), Anna Maaser (a2) (a3), Dmitry Prokopenko (a1), Heide Loehlein Fier (a1) (a4) and Christoph Lange (a4) (a5)...

Abstract

VEGAS (versatile gene-based association study) is a popular methodological framework to perform gene-based tests based on summary statistics from single-variant analyses. The approach incorporates linkage disequilibrium information from reference panels to account for the correlation of test statistics. The gene-based test can utilize three different types of tests. In 2015, the improved framework VEGAS2, using more detailed reference panels, was published. Both versions provide user-friendly web- and offline-based tools for the analysis. However, the implementation of the popular top-percentage test is erroneous in both versions. The p values provided by VEGAS2 are deflated/anti-conservative. Based on real data examples, we demonstrate that this can increase substantially the rate of false-positive findings and can lead to inconsistencies between different test options. We also provide code that allows the user of VEGAS to compute correct p values.

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Copyright

Corresponding author

address for correspondence: Christoph Lange, Department of Biostatistics, Harvard TH Chan School of Public Health, 665 Huntington Avenue, Building I Room 419, Boston, Massachusetts 02115, USA. E-mail: langech2007@gmail.com

References

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1000 Genomes Project Consortium. (2012). An integrated map of genetic variation from 1,092 human genomes. Nature, 491, 5665.
International HapMap 3 Consortium. (2010). Integrating common and rare genetic variation in diverse human populations. Nature, 467, 5258.
Liu, J. Z., McRae, A. F., Nyholt, D. R., Medland, S. E., Wray, N. R., Brown, K. M., . . . MacGregor, S. (2010). A versatile gene-based test for genome-wide association studies. American Journal of Human Genetics, 87, 139145.
Mishra, A., & MacGregor, S. (2015). VEGAS2: Software for more flexible gene-based testing. Twin Research and Human Genetics, 18, 8691.
Psychiatric GWAS Consortium Bipolar Disorder Working Group. (2011). Large-scale genome-wide association analysis of bipolar disorder identifies a new susceptibility locus near ODZ4. Nature Genetics, 43, 977983.

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