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Related Experiment Video

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Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

Two-stage case-control designs for rare genetic variants.

Daniel J Schaid¹, Jason P Sinnwell

¹Division of Biomedical Statistics and Informatics, Harwick 7, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA. schaid@mayo.edu

|March 31, 2010

Summary

This study introduces an efficient two-stage design for identifying rare genetic variants associated with common diseases, optimizing cost and sample size. The method ensures accurate results while allowing for early study termination if few variants are found.

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Area of Science:

Genetics
Statistical genetics
Computational biology

Background:

Identifying associations between rare genetic variants and common diseases is crucial but faces cost challenges.
Existing methods may not be cost-effective for screening rare variants.
Efficient study designs are needed to balance discovery and resource allocation.

Purpose of the Study:

To develop and evaluate an efficient two-stage study design for detecting rare genetic variants associated with common diseases.
To optimize study parameters for minimizing sample size while maintaining statistical power.
To provide guidance for designing cost-effective genetic association studies.

Main Methods:

A two-stage screening design is proposed, starting with diseased cases in stage-1.
Variants identified in stage-1 are further analyzed in stage-2 with cases and controls.
An exact test correcting for stage-1 ascertainment is used for variant frequency comparison.

Main Results:

The proposed method demonstrates conservative Type-I error rates, comparable to Fisher's exact test.
Study stopping probability at stage-1 is influenced by the number of cases, continuation threshold, and carrier probability.
Simulations illustrate the impact of these factors on stage-2 power and overall study efficiency.

Conclusions:

The two-stage design offers an efficient approach to studying rare variants in common diseases.
The method provides a balance between early stopping and robust statistical analysis.
Guidance is offered for optimizing study design to minimize expected sample size and achieve desired power.