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Power analysis and sample size estimation for sequence-based association studies.


ABSTRACT:

Motivation

Statistical methods have been developed to test for complex trait rare variant (RV) associations, in which variants are aggregated across a region, which is typically a gene. Power analysis and sample size estimation for sequence-based RV association studies are challenging because of the necessity to realistically model the underlying allelic architecture of complex diseases within a suitable analytical framework to assess the performance of a variety of RV association methods in an unbiased manner.

Summary

We developed SEQPower, a software package to perform statistical power analysis for sequence-based association data under a variety of genetic variant and disease phenotype models. It aids epidemiologists in determining the best study design, sample size and statistical tests for sequence-based association studies. It also provides biostatisticians with a platform to fairly compare RV association methods and to validate and assess novel association tests.

Availability and implementation

The SEQPower program, source code, multi-platform executables, documentation, list of association tests, examples and tutorials are available at http://bioinformatics.org/spower.

SUBMITTER: Wang GT 

PROVIDER: S-EPMC4133582 | biostudies-literature | 2014 Aug

REPOSITORIES: biostudies-literature

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Power analysis and sample size estimation for sequence-based association studies.

Wang Gao T GT   Li Biao B   Santos-Cortez Regie P Lyn RP   Peng Bo B   Leal Suzanne M SM  

Bioinformatics (Oxford, England) 20140428 16


<h4>Motivation</h4>Statistical methods have been developed to test for complex trait rare variant (RV) associations, in which variants are aggregated across a region, which is typically a gene. Power analysis and sample size estimation for sequence-based RV association studies are challenging because of the necessity to realistically model the underlying allelic architecture of complex diseases within a suitable analytical framework to assess the performance of a variety of RV association method  ...[more]

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