Research Projects

Jun 2023 - Present

Developing Pipeline for Analyzing Next Generation Cut & Tag Technology Hiplex.app

Developing peak calling method for next generation Cut & Tag technology which is able to measure multiple targets simultaneously

Analyzing the signals of epigenomic biomarker pairs in different genomic bins.

Exploring the efficacy of single-cell next generation Cut & Tag data for cell-type identification.

Sep 2021 - Present

Proteomic Associations with Chronic Kidney Disease (CKD)

Evaluating the association between estimated glomerular filtration rate (eGFR), CKD and protein abundance.

Detecting modules of proteins utilizing WGCNA (Langfelder, et al., 2008) and further exploring the pathways enriched in the modules significantly associated with eGFR and CKD.

Nov 2018 - Dec 2020, Oct 2022 - May 2023

Effects of α-globin Copy Number Variation (CNV) on Complex Traits

Exploring if α-globin copy number variation modifies the effects of the β-globin variant rs334 (sickle cell disease defining variant) or an independent single nucleotide variant in the MCS-R2 enhancer region on complex traits associated with sickle cell disease or trait such as stroke, kidney disease, and blood cell traits in Black and Hispanic/Latino participants utilizing generalized linear mixed models.

Called α-globin copy number variation utilizing Genome STRiP.

Developed whole genome sequencing based CNV imputation pipeline utilizing Minimac4 and BEAGLE.

Sep 2022 - May 2023

Cohort-Agnostic Genotype Imputation Quality Calibration

Developing semi-supervised learning based cohort-agnostic method for calibrating genotype imputation quality.

Exploring the potential of multi-task learning frameworks to enhance performance of our calibration model.

Mar 2020 - Apr 2024

Whole Genome Sequence Analysis of Inflammation Traits

Found MMP9 locus significantly associated with Matrix Metallopeptidase 9 (MMP9) trait.

Revealed 22 distinct and putatively novel signals across 8 previously identified loci for 6 inflammation traits.

Sep 2018 - Nov 2022

Multi-Omics Integration Analysis

Improved the Sparse Multiple Canonical Correlation Analysis (Witten, et al., 2009) method by enhancing the orthogonality of the canonical variables.

Developed the Supervised Sparse Multiple Canonical Correlation Analysis method.

Found pronounced effect of blood cell counts on protein abundance in two independent cohort studies.

Evaluated the advantages of our method over principal component analysis on explaining the variation of outcomes when assay-specific batch effects are present.