Kipper Fletez‐Brant

GEMS associates GWAS variants with cell types using sequence-to-function predictions, revealing cell-type-specific mechanisms for disease risk variants.

gRely provides reliability scores for sequence-to-expression models, improving prediction filtering beyond magnitude thresholds in low-magnitude regimes.

scEPS integrates GWAS and single-cell data to identify disease-associated cell neighborhoods by testing gene expression variance explained in disease contexts.

This paper introduces CompBioBench, a benchmark for evaluating agentic systems in computational biology, showing strong performance across diverse tasks.

The paper benchmarks five machine learning-based variant annotation methods for rare variant association testing across 350,377 UK Biobank participants, finding CADD provides best signal separation and GPN-MSA highest enrichment for loss-of-function intolerant genes.

This study compares polygenic risk scores for Parkinson's disease across seven ancestries, finding varying predictive accuracy and highlighting the need for ancestry-specific models.

This study compares eQTL discovery in African and European ancestry cohorts, finding more eQTLs in African samples and improved GWAS variant-to-gene mapping using African eQTLs.

MUSSEL improves polygenic risk prediction across populations by integrating GWAS summary statistics and using Bayesian hierarchical modeling with ensemble learning.

The paper introduces BNBC, a normalization and batch correction method for Hi-C data, improving cross-sample comparisons and analyses.

This paper conducts a multi-ancestry genome-wide meta-analysis of Parkinson's disease, identifying 78 independent loci and 23 genes associated with PD risk.

The paper introduces CT-SLEB, a method for multi-ancestry polygenic prediction that improves performance in non-European populations using GWAS summary statistics and simulation studies.

This study identifies 49 genetic loci associated with sleep apnoea risk using multi-trait GWAS, with 29 replicated in a large cohort, and finds genetic correlations with several complex traits.

This study conducts a genome-wide association study to identify genetic variants linked to musical beat synchronization, finding high polygenicity with 69 significant loci and heritability estimates of 13%-16%.

The paper identifies a genetic association between the UGT2A1/UGT2A2 locus and COVID-19-related anosmia using a trans-ethnic GWAS.

The paper identifies sex-differential participation bias in genetic studies by performing GWAS on sex in 3.3 million individuals, finding 158 loci associated with sex and highlighting traits like BMI that may influence participation.

This study identifies genetic loci associated with daytime napping and finds potential causal links between napping and cardiometabolic traits.

The paper identifies HLA-B*55:01 as a genetic risk factor for penicillin allergy through genome-wide analysis of electronic health records and imputed HLA data.

This study identifies one known and two novel genetic variants associated with heart failure through GWAS and multi-omic analyses, revealing potential causal mechanisms and shared heritability with musculoskeletal traits.

This study identifies DNA sequence variants that influence 3D chromatin conformation and links them to gene expression and disease risk.