Table 2. Performance comparisons between untuned autoencoder (AE) and HMM-based imputation tools (Minimac4, Beagle5, and Impute5).

Average r-squared per variant was extracted from each genomic segment of chromosome 22. We applied Wilcoxon rank-sum tests to compare the HMM-based tools to the reference tuned autoencoder (AE). * represents p-values ≤0.05, ** indicates p-values ≤0.001, and *** indicates p-values ≤0.0001.

	MESA	Wellderly	HGDP	Affymetrix 6.0	UKB Axiom	Omni 1.5 M	Combined
AE (untuned)	0.303±0.008	0.470±0.009	0.285±0.006	0.339±0.008	0.356±0.007	0.362±0.008	0.352±0.008
Minimac4	0.337±0.007*	0.471±0.008	0.314±0.006**	0.352±0.008	0.370±0.006	0.400±0.007**	0.374±0.007*
Beagle5	0.336±0.007*	0.460±0.008	0.296±0.005	0.342±0.007	0.367±0.006	0.384±0.007*	0.364±0.007
Impute5	0.326±0.007*	0.458±0.008	0.289±0.006	0.336±0.008	0.354±0.006	0.383±0.008*	0.358±0.007