Kirk C. Wilhelmsen

This study identifies convergent genetic pathways for cannabis use disorder across three populations, highlighting shared and population-specific genetic factors.

This study identifies pleiotropic loci for cannabis use disorder severity in three high-risk populations using GWAS data and machine learning, finding shared pathways and tissue-specific expression patterns.

TWO-SIGMA-G tests gene sets in scRNA-seq data by accounting for gene and cell correlations, showing improved power and error control in simulations and real datasets.

This study shows exome sequencing of cell-free DNA is limited by technical issues and sampling challenges, making it unsuitable for noninvasive prenatal detection of single-gene disorders.

SMNN improves batch effect correction in scRNA-seq by using supervised mutual nearest neighbor detection within cell types, leading to better merging and retention of cell-type specific features.

The paper introduces CALF, a linear regression method that outperforms LASSO in several metrics on real medical data.

This study identifies the causal mechanism of X-linked Dystonia-Parkinsonism (XDP) by integrating genome and transcriptome assembly, revealing a SVA insertion causing intron retention and TAF1 dysfunction.