Yuxin Zou

The paper introduces mvSuSiE, a multi-trait fine-mapping method that improves causal SNP identification by jointly analyzing multiple traits, discovering more causal SNPs and narrower credible sets compared to single-trait approaches.

The paper introduces SBAT, a method for joint testing of rare variant burden scores, showing it is well calibrated and outperforms existing tests in some scenarios.

The paper compares the effectiveness of whole genome sequencing, whole exome sequencing with imputation, and array genotyping in detecting genetic associations across 100 complex traits in the UK Biobank, finding that WES+IMP provides similar signal yield to WGS with greater efficiency.

The paper introduces a flexible empirical Bayes method for multivariate multiple regression to improve prediction of multi-tissue gene expression from genotypes.

This paper extends the SuSiE model to work with summary data, showing it is competitive with existing methods in speed and accuracy for fine-mapping genetic variants.

The paper genotypes and sequences 140,000 adults from the Mexico City Prospective Study, revealing ancestry diversity and developing imputation resources for genetic studies.

The paper uses bulk RNA-seq data to estimate cell type abundances and identifies cell type interaction QTLs that provide finer resolution of tissue specificity than bulk cis-eQTLs.

The paper quantifies protein levels across 32 human tissues and compares them to transcriptome data, revealing insights into post-transcriptional regulation and disease mechanisms.

GTEx v8 maps expression and splicing QTLs in 49 tissues from 838 donors: cis-eQTLs cover 94.7% of protein-coding genes, and cross-tissue QTL sharing mirrors cell-type composition.