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

Bioinformatics. 2014 Aug 15;30(16):2377-8. doi: 10.1093/bioinformatics/btu296. Epub 2014 Apr 28.


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.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Alleles
  • Data Interpretation, Statistical
  • Disease / genetics
  • Genetic Association Studies / methods*
  • Genetic Variation*
  • Humans
  • Phenotype
  • Sample Size
  • Sequence Analysis, DNA / methods*
  • Software*