Rounak Dey

A Scalable Framework for Identifying Allelic Series from Summary Statistics

The paper introduces COAST-SS, a method to identify allelic series using summary statistics, showing it is effective and robust to LD matrix misspecification.

A statistical framework for powerful multi-trait rare variant analysis in large-scale whole-genome sequencing studies

The paper introduces MultiSTAAR, a statistical framework for multi-trait rare variant analysis in WGS studies, identifying new lipid trait associations in diverse populations.

Pitfalls in performing genome-wide association studies on ratio traits

This paper shows that genome-wide association studies on ratio traits can be misleading, as associations may be driven by the denominator rather than the numerator, and proposes a method to correct for collider bias.

Causal considerations can determine the utility of machine learning assisted GWAS

This study shows that machine learning-derived phenotypes for GWAS can lead to false discoveries depending on their causal relationship with the target phenotype and environment.

A framework for detecting noncoding rare variant associations of large-scale whole-genome sequencing studies

The paper introduces a framework for detecting noncoding rare variant associations using whole-genome sequencing data, applying it to lipid traits in the TOPMed program.

Efficient mixed model approach for large-scale genome-wide association studies of ordinal categorical phenotypes

The paper introduces POLMM, a mixed model for ordinal categorical phenotypes in GWAS, showing it is computationally efficient, controls type I error, and identifies more significant variants than existing methods.

A versatile toolkit for molecular QTL mapping and meta-analysis at scale

APEX is a toolkit for molecular QTL mapping and meta-analysis that improves scalability and accuracy for large datasets and summary statistics.

An efficient and accurate frailty model approach for genome-wide survival association analysis controlling for population structure and relatedness in large-scale biobanks

The paper introduces a frailty model for genome-wide survival analysis in large biobanks, handling population structure and relatedness, and demonstrates its performance on real-world datasets.

Fast and robust ancestry prediction using principal component analysis

This paper introduces two methods to improve ancestry prediction in GWAS by reducing bias and computational cost compared to existing approaches.

Technical Note: Efficient and accurate estimation of genotype odds ratios in biobank-based unbalanced case-control studies

The paper introduces a scalable method to accurately estimate genotype odds ratios in unbalanced biobank-based case-control studies, improving computational efficiency compared to existing methods.

Efficiently controlling for case-control imbalance and sample relatedness in large-scale genetic association studies

This paper introduces SAIGE, a method that improves the accuracy of genetic association tests in unbalanced case-control studies by using saddlepoint approximation, and demonstrates its effectiveness on UK Biobank data.

Genome-wide association study of 1 million people identifies 111 loci for atrial fibrillation

This study identifies 111 genetic loci and 163 risk variants associated with atrial fibrillation using a GWAS of over 1 million individuals.

A fast and accurate algorithm to test for binary phenotypes and its application to PheWAS

The paper introduces a fast score test-based method for PheWAS with unbalanced case-control ratios, showing it controls type I error and replicates known associations.