Fig. 1: Workflow of the SPAGxECCT framework.

The SPAGxECCT framework consists of two main steps: (1) fitting a genotype-independent model to calculate residuals, and (2) computing test statistics based on p values for marginal genetic effects and associating traits of interest with single genetic variant by approximating the null distribution of test statistics. Leveraging a hybrid strategy combining normal distribution approximation and saddlepoint approximation, SPAGxECCT is scalable for analyzing large-scale biobank data and maintains high accuracy for rare genetic variants, even under unbalanced phenotypic distributions.