Skip Navigation
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.


The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Your Environment. Your Health.

Publication Detail

Title: A robust association test for detecting genetic variants with heterogeneous effects.

Authors: Yu, Kai; Zhang, Han; Wheeler, William; Horne, Hisani N; Chen, Jinbo; Figueroa, Jonine D

Published In Biostatistics, (2015 Jan)

Abstract: One common strategy for detecting disease-associated genetic markers is to compare the genotype distributions between cases and controls, where cases have been diagnosed as having the disease condition. In a study of a complex disease with a heterogeneous etiology, the sampled case group most likely consists of people having different disease subtypes. If we conduct an association test by treating all cases as a single group, we maximize our chance of finding genetic risk factors with a homogeneous effect, regardless of the underlying disease etiology. However, this strategy might diminish the power for detecting risk factors whose effect size varies by disease subtype. We propose a robust statistical procedure to identify genetic risk factors that have either a uniform effect for all disease subtypes or heterogeneous effects across different subtypes, in situations where the subtypes are not predefined but can be characterized roughly by a set of clinical and/or pathologic markers. We demonstrate the advantage of the new procedure through numeric simulation studies and an application to a breast cancer study.

PubMed ID: 25057183 Exiting the NIEHS site

MeSH Terms: Breast Neoplasms/genetics; Data Interpretation, Statistical*; Female; Genetic Markers; Genetic Variation/genetics*; Genome-Wide Association Study/methods*; Humans; Models, Genetic*; Risk Factors

to Top