Lei Sun

The paper assesses Hardy-Weinberg equilibrium deviations in whole genome sequence data from the 1000 Genomes Project, identifying SNPs with technical rather than biological deviations.

The paper introduces effect size-based methods to rank transcription factor binding motifs, showing they outperform p-value rankings under heterogeneous sample sizes.

The paper develops a statistical framework for Hardy-Weinberg equilibrium testing on the X chromosome, showing that existing methods can have inflated type I error or misleading results when sex differences in minor allele frequency are present.

This study investigates the role of SEPT9 in intestinal epithelial barrier integrity and inflammation, finding that its loss disrupts tight junctions and increases susceptibility to colitis.

This study performs an X chromosome-wide association study (XWAS) in ASD, identifying 59 variants associated with ASD, including novel candidate genes like FGF13.

The paper develops eigen-polygenic risk scores (ePRSs) from clustered subnetworks of single-trait PRSs and shows they improve prediction of Alzheimer's Disease and related phenotypes.

The paper investigates the genetic impact of the X-chromosome and sex differences in the human brain, identifying 72 genome-wide significant trait-locus pairs linked to brain-related disorders.

The paper proposes a joint statistical test that integrates association evidence with Hardy-Weinberg disequilibrium differences between case and control groups to improve detection of disease susceptibility loci.

The paper re-evaluates the inclusion of sex chromosomes in GWAS, finding persistent underrepresentation and proposing recommendations for improvement.

The paper establishes analytical connections between different genetic association tests for population- and family-based studies, helping practitioners choose appropriate tests.

This paper introduces a sex-combined interaction analysis method for genetic association studies, identifying new loci for testosterone levels in the UK Biobank data.

The paper identifies significant sex differences in minor allele frequencies for X chromosome variants in the 1000 Genomes Project data, highlighting the need to account for these differences in future analyses.

The paper uses linked-read sequencing to phase alleles in 477 CF patients, revealing haplotypes that explain disease mechanisms and contribute to understanding complex traits.

gJLS2 enables joint analysis of location and scale in genome-wide studies to detect markers influencing quantitative traits through mean and variance, outperforming single tests.

The paper introduces a new colocalization method, SS2, to identify the gene responsible for a CF lung disease locus, finding significant colocalization with MUC4.

This paper introduces a generalized robust allele-based genetic association test that accounts for HWE violations, continuous traits, covariates, and sample correlation, and shows it encompasses classical allelic tests as a special case.

This paper assesses the statistical power of case-control genomic studies for identifying host genetic factors associated with COVID-19 susceptibility and severity using simulations and current epidemiological estimates.

The paper introduces a summary statistics-based regression framework for set-based association tests, improving power through precision matrix transformation and demonstrating its effectiveness via simulations and applications.

LocusFocus is a web tool that tests colocalization between GWAS and eQTL data to identify relevant genes and tissues for GWAS loci.

The paper investigates X-chromosome variance heterogeneity in quantitative traits using generalized Levene's test and sex-stratified analysis, finding possible polygenic structure for human height variance.

TRUFFLE detects IBD segments and estimates relatedness in un-phased genetic data efficiently and accurately, outperforming existing methods in speed and reducing false positives.

The paper proposes a unifying reverse regression framework for genetic association studies and allele frequency estimation, showing its ability to adjust for Hardy-Weinberg equilibrium and connect with existing allele-frequency estimators.

The paper evaluates type 1 error rate control in statistical tests using different simulation designs, showing that empirical null designs reveal inflated error rates compared to theoretical null designs.