Extended Data Fig. 5: Influence of numbers of leading eigenvalues on bias of genetic covariance.
From: An enhanced framework for local genetic correlation analysis
We randomly selected 16 loci. After performing eigen-decomposition to the LD matrix, leading eigenvalues explaining different amount of variances of the LD matrix and their corresponding eigenvectors were taken to approximate the LD matrix. Each boxplot shows the distribution of genetic covariance bias across simulations, with the box spanning the first quartile to the third quartile (Q1–Q3) and the horizontal line indicating the median.
