Tanushree Haldar

This paper introduces a TWAS method that adjusts for predicted expression uncertainty, improving type I error control and effect size estimation compared to traditional approaches.

This study quantifies the heritability of drug response to statins, metformin, warfarin, and methotrexate in UK Biobank participants and identifies genetic modifiers of drug effects and side effects.

This paper introduces a unified Bayesian approach for transcriptome-wide association studies (TWAS) that improves accuracy by jointly modeling transcriptome and GWAS data, showing better performance in gene-trait association detection.

This paper introduces a statistical method to identify tissue-specific genetic contributions to complex traits at the individual level using eQTLs and applies it to BMI and WHRadjBMI in the UK Biobank.

The paper proposes a two-step method to detect gene-environment interactions across multiple phenotypes, showing improved power in simulations and identifying significant signals in lipid data from UK Biobank.

This paper introduces CPBayes, a Bayesian method for detecting pleiotropic genetic associations across multiple traits, showing improved accuracy over existing methods in both simulations and real data.