G-STRATEGY: Optimal Selection of Individuals for Sequencing in Genetic Association Studies

Miaoyan Wang, Johanna Jakobsdottir, Albert V. Smith, Mary Sara McPeek*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)


In a large-scale genetic association study, the number of phenotyped individuals available for sequencing may, in some cases, be greater than the study's sequencing budget will allow. In that case, it can be important to prioritize individuals for sequencing in a way that optimizes power for association with the trait. Suppose a cohort of phenotyped individuals is available, with some subset of them possibly already sequenced, and one wants to choose an additional fixed-size subset of individuals to sequence in such a way that the power to detect association is maximized. When the phenotyped sample includes related individuals, power for association can be gained by including partial information, such as phenotype data of ungenotyped relatives, in the analysis, and this should be taken into account when assessing whom to sequence. We propose G-STRATEGY, which uses simulated annealing to choose a subset of individuals for sequencing that maximizes the expected power for association. In simulations, G-STRATEGY performs extremely well for a range of complex disease models and outperforms other strategies with, in many cases, relative power increases of 20–40% over the next best strategy, while maintaining correct type 1 error. G-STRATEGY is computationally feasible even for large datasets and complex pedigrees. We apply G-STRATEGY to data on high-density lipoprotein and low-density lipoprotein from the AGES-Reykjavik and REFINE-Reykjavik studies, in which G-STRATEGY is able to closely approximate the power of sequencing the full sample by selecting for sequencing a only small subset of the individuals.

Original languageEnglish
Pages (from-to)446-460
Number of pages15
JournalGenetic Epidemiology
Issue number6
Publication statusPublished - 1 Sept 2016

Bibliographical note

Publisher Copyright:

Other keywords

  • association mapping
  • family data
  • selective genotyping
  • sequence
  • simulated annealing


Dive into the research topics of 'G-STRATEGY: Optimal Selection of Individuals for Sequencing in Genetic Association Studies'. Together they form a unique fingerprint.

Cite this