Kelan G. Tantisira

This paper develops a multimodal framework to prioritize causal genes in childhood-onset asthma by integrating GWAS, bulk eQTL, and single-cell eQTL data, revealing key immune and metabolic genes and improving risk prediction across cohorts.

This study uses single-cell RNA sequencing to analyze sputum cells from asthma patients and controls, identifying dysregulated pathways and communication networks involved in asthma pathogenesis.

COMPASS identifies and quantifies small RNAs from sequencing data, showing greater diversity and abundance compared to existing tools in a human serum dataset.

This paper introduces six new statistical tests for differential correlation networks that are computationally efficient and outperform existing methods in simulations and real data analysis.

The paper identifies high-impact variants in pharmacogenomic genes using whole-genome sequencing data from the 1000 Genomes Project.

The paper introduces a model-based clustering method to detect differentially variable microRNAs, outperforming the probe-wise F test and identifying 7 novel microRNAs in hepatocellular carcinoma.

This study identifies pharmacogenetic variants associated with albuterol bronchodilator response in minority children with asthma using whole genome sequencing.