We develop quantitative and computational methods and tools to sift through the vast amounts of genomic and other high dimensional data with the goal of making discoveries that can be translated to improve human health.
University of Chicago
Chicago
PhD - Statistics
2005
A multi-tissue, splicing-based joint transcriptome-wide association study identifies susceptibility genes for breast cancer.
A multi-tissue, splicing-based joint transcriptome-wide association study identifies susceptibility genes for breast cancer. Am J Hum Genet. 2024 06 06; 111(6):1100-1113.
PMID: 38733992
Transcriptome-wide association study of the plasma proteome reveals cis and trans regulatory mechanisms underlying complex traits.
Transcriptome-wide association study of the plasma proteome reveals cis and trans regulatory mechanisms underlying complex traits. Am J Hum Genet. 2024 03 07; 111(3):445-455.
PMID: 38320554
On the problem of inflation in transcriptome-wide association studies.
On the problem of inflation in transcriptome-wide association studies. bioRxiv. 2023 Oct 20.
PMID: 37904952
Predicted Proteome Association Studies of Breast, Prostate, Ovarian, and Endometrial Cancers Implicate Plasma Protein Regulation in Cancer Susceptibility.
Predicted Proteome Association Studies of Breast, Prostate, Ovarian, and Endometrial Cancers Implicate Plasma Protein Regulation in Cancer Susceptibility. Cancer Epidemiol Biomarkers Prev. 2023 09 01; 32(9):1198-1207.
PMID: 37409955
Revealing polygenic pleiotropy using genetic risk scores for asthma.
Revealing polygenic pleiotropy using genetic risk scores for asthma. HGG Adv. 2023 10 12; 4(4):100233.
PMID: 37663543
Multivariate adaptive shrinkage improves cross-population transcriptome prediction and association studies in underrepresented populations.
Multivariate adaptive shrinkage improves cross-population transcriptome prediction and association studies in underrepresented populations. HGG Adv. 2023 Oct 12; 4(4):100216.
PMID: 37869564
Predicting molecular mechanisms of hereditary diseases by using their tissue-selective manifestation.
Predicting molecular mechanisms of hereditary diseases by using their tissue-selective manifestation. Mol Syst Biol. 2023 08 08; 19(8):e11407.
PMID: 37232043
Multivariate adaptive shrinkage improves cross-population transcriptome prediction for transcriptome-wide association studies in underrepresented populations.
Multivariate adaptive shrinkage improves cross-population transcriptome prediction for transcriptome-wide association studies in underrepresented populations. bioRxiv. 2023 May 20.
PMID: 36798214
A joint transcriptome-wide association study across multiple tissues identifies candidate breast cancer susceptibility genes.
A joint transcriptome-wide association study across multiple tissues identifies candidate breast cancer susceptibility genes. Am J Hum Genet. 2023 06 01; 110(6):950-962.
PMID: 37164006
Probabilistic integration of transcriptome-wide association studies and colocalization analysis identifies key molecular pathways of complex traits.
Probabilistic integration of transcriptome-wide association studies and colocalization analysis identifies key molecular pathways of complex traits. Am J Hum Genet. 2023 01 05; 110(1):44-57.
PMID: 36608684