Sanghun Lee

Polygenic risk scores associate with asthma phenotypes and proteomic analyses implicate IL1R1 in two family-based studies

This study uses polygenic risk scores and proteomic analysis to identify genetic and molecular associations with asthma in two family-based cohorts, highlighting IL1R1's role in asthma pathogenesis.

A Comparative Genomic Analysis of Left- and Right-Sided Colon Cancer Using Real-World Data from the AACR Project GENIE BPC Dataset

This study compares genomic features of left- and right-sided colon cancers using real-world data, finding significant differences in mutation burdens and survival outcomes.

Unsupervised outlier detection applied to SARS-CoV-2 nucleotide sequences can identify sequences of common variants and other variants of interest

A robust and adaptive framework for interaction testing in quantitative traits between multiple genetic loci and exposure variables

RITSS identifies gene-environment interactions in quantitative traits using sample splitting and robust statistics, finding significant interactions in lung function and height data.

Region-based analysis of rare genomic variants in whole-genome sequencing datasets reveal two novel Alzheimer's disease-associated genes: DTNB and DLG2

This study identifies two novel Alzheimer's disease-associated genes, DTNB and DLG2, by analyzing rare variants in whole-genome sequencing data from AD family datasets.

Unsupervised genome-wide cluster analysis: nucleotide sequences of the omicron variant of SARS-CoV-2 are similar to sequences from early 2020

The paper uses unsupervised cluster analysis to show that omicron variant SARS-CoV-2 sequences are most similar to early 2020 sequences, suggesting long-term circulation.

Unsupervised cluster analysis of SARS-CoV-2 genomes reflects its geographic progression and identifies distinct genetic subgroups of SARS-CoV-2 virus

The paper uses unsupervised clustering of SARS-CoV-2 genomes to show geographic progression and identify genetic subgroups.

Two mutations in the SARS-CoV-2 spike protein and RNA polymerase complex are associated with COVID-19 mortality risk

The paper identifies two SARS-CoV-2 genome loci associated with increased COVID-19 mortality risk using logistic regression on whole-genome sequencing data.