Reply To: Re-Evaluating Local Genetic Correlation Analysis in the HDL Framework
Abstract
The LAVA method has been proposed for detecting local genetic correlations between traits. We show, using theoretical analysis and simulations, that LAVA’s “fixed-effects” model does not estimate genetic correlation in the statistical genetics sense, but instead detects the presence of regional genetic effects. This mis-specification leads to inflated type-I error under the null, particularly when causal variants are sparse, and can produce apparent “correlations” arising solely from unshared, trait-specific signals. In contrast, the random-effects model implemented in HDL-L correctly targets variant-level genetic correlation and remains well-calibrated. Our results indicate that LAVA findings may be widely misinterpreted, and we recommend caution and the use of random-effects–based approaches such as HDL-L for valid inference.
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