Wednesday, 27 June 2012

Statistical Tests for Detecting Rare Variants Using Variance-Stabilising Transformations.

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1. Ann Hum Genet. 2012 Jun 25. doi: 10.1111/j.1469-1809.2012.00718.x. [Epub ahead of print]

Statistical Tests for Detecting Rare Variants Using Variance-Stabilising Transformations.

Wang K, Fingert JH.


Department of Biostatistics, College of Public Health, The University of Iowa, Iowa City, IA, USA Department of Ophthalmology and Visual Sciences, Carver College of Medicine, The University of Iowa, IA, USA.


Next generation sequencing holds great promise for detecting rare variants underlying complex human traits. Due to their extremely low allele frequencies, the normality approximation for a proportion no longer works well. The Fisher's exact method appears to be suitable but it is conservative. We investigate the utility of various variance-stabilising transformations in single marker association analysis on rare variants. Unlike a proportion itself, the variance of the transformed proportions no longer depends on the proportion, making application of such transformations to rare variant association analysis extremely appealing. Simulation studies demonstrate that tests based on such transformations are more powerful than the Fisher's exact test while controlling for type I error rate. Based on theoretical considerations and results from simulation studies, we recommend the test based on the Anscombe transformation over tests with other transformations.

© 2012 The Authors Annals of Human Genetics © 2012 Blackwell Publishing Ltd/University College London.

PMID: 22724536 [PubMed - as supplied by publisher]

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