Masao Ueki

This study identifies scenarios where population stratification inflates gene-gene interaction test statistics and proposes a method to control false positives by adding a SNP-population structure interaction term to regression models.

This paper constructs a fine-scale genetic map of the Japanese population using whole-genome sequencing data, identifies recombination hotspots, and shows improved haplotype phasing and imputation accuracy.

The paper uses clustering and genome-wide association studies to identify subgroups in autism spectrum disorder and finds significant loci associated with these subgroups.

This study develops a deep learning method to automatically extract explainable features from histopathological images, achieving higher accuracy than human pathologists in predicting prostate cancer recurrence.

The paper constructs a population-level allele frequency panel of 3,552 Japanese individuals using a standardized pipeline and makes it publicly available.