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

نویسندگان

  • Gao T. Wang
  • Biao Li
  • Regie P. Lyn Santos-Cortez
  • Bo Peng
  • Suzanne M. Leal
چکیده

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.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Sample size estimation in epidemiologic studies

This review basically provided a conceptual framework for sample size calculation in epidemiologic studies with various designs and outcomes. The formula requirement of sample size was drawn based on statistical principles for both descriptive and comparative studies. The required sample size was estimated and presented graphically with different effect sizes and power of statistical test at 95...

متن کامل

Bayesian Sample size Determination for Longitudinal Studies with Continuous Response using Marginal Models

Introduction Longitudinal study designs are common in a lot of scientific researches, especially in medical, social and economic sciences. The reason is that longitudinal studies allow researchers to measure changes of each individual over time and often have higher statistical power than cross-sectional studies. Choosing an appropriate sample size is a crucial step in a successful study. A st...

متن کامل

Bayesian Sample Size Determination for Joint Modeling of Longitudinal Measurements and Survival Data

A longitudinal study refers to collection of a response variable and possibly some explanatory variables at multiple follow-up times. In many clinical studies with longitudinal measurements, the response variable, for each patient is collected as long as an event of interest, which considered as clinical end point, occurs. Joint modeling of continuous longitudinal measurements and survival time...

متن کامل

Power and sample size calculations for designing rare variant sequenc - ing association studies

Recently, Wu et al. [4] have proposed the sequence kernel machine test (SKAT) to test association between genetic variants in a gene or region and a continuous or binary trait. SKAT, which uses the kernel machine regression framework, is very flexible and computationally efficient. From extensive simulation studies and real data application, it has been shown that SKAT is more powerful than the...

متن کامل

Determining the Sample size for Estimation of the CCC-R Control Chart Parameters Based on Estimation Costs

In today's highly competitive industrial environment due to fast technology development, quality practitioners will to detect out-of-control situations and take actions whenever is necessary as soon as possible. Accordingly, new statistical procedures have been enhanced incessantly both to handle high yield processes along with looking for methods of minimizing all quality cost. CCC-r chart, th...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • Bioinformatics

دوره 30 16  شماره 

صفحات  -

تاریخ انتشار 2014