A Bayesian test to identify variance effects

A Bayesian test to identify variance effects
Bianca Dumitrascu, Gregory Darnell, Julien Ayroles, Barbara E Engelhardt

Identifying genetic variants that regulate quantitative traits, or QTLs, is the primary focus of the field of statistical genetics. Most current methods are limited to identifying mean effects, or associations between genotype and the mean value of a quantitative trait. It is possible, however, that a genetic variant may affect the variance of the quantitative trait in lieu of, or in addition to, affecting the trait mean. Here, we develop a general methodological approach to identifying covariates with variance effects on a quantitative trait using a Bayesian heteroskedastic linear regression model. We show that our Bayesian test for heteroskedasticity (BTH) outperforms classical tests for differences in variation across a large range of simulations drawn from scenarios common to the analysis of quantitative traits. We apply BTH to methylation QTL study data and expression QTL study data to identify variance QTLs. When compared with three tests for heteroskedasticity used in genomics, we illustrate the benefits of using our approach, including avoiding overfitting by incorporating uncertainty and flexibly identifying heteroskedastic effects.


Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out / Change )

Twitter picture

You are commenting using your Twitter account. Log Out / Change )

Facebook photo

You are commenting using your Facebook account. Log Out / Change )

Google+ photo

You are commenting using your Google+ account. Log Out / Change )

Connecting to %s