David V. Conti

Praxis-BGM: Clustering of Omics Data Using Semi-Supervised Transfer Learning for Gaussian Mixture Models via Natural-Gradient Variational Inference

An Efficient Lasso Framework for Admixture-Aware Polygenic Scores

HAUDI improves polygenic score construction for admixed populations by efficiently extending the GAUDI method to multi-way admixture with faster computation and better performance.

Transcriptome-Wide Association Analysis Identifies Novel Candidate Susceptibility Genes for Prostate-Specific Antigen Levels in Men Without Prostate Cancer

Admix-kit: An Integrated Toolkit and Pipeline for Genetic Analyses of Admixed Populations

Admix-kit provides tools for genetic analysis of admixed populations, enabling simulation, association testing, and polygenic scoring.

Genome-wide association study of prostate-specific antigen levels in 392,522 men identifies new loci and improves cross-ancestry prediction

This study identifies 447 new genetic variants associated with prostate-specific antigen levels across multiple ancestries and shows improved cross-ancestry prediction of PSA, with implications for personalized prostate cancer screening.

Estimating heritability explained by local ancestry and evaluating stratification bias in admixture mapping from summary statistics

This paper introduces HAMSTA, a method to estimate heritability from admixture mapping summary statistics while adjusting for ancestral stratification bias, and applies it to African American datasets.

Genetically Adjusted PSA Levels for Prostate Cancer Screening

This study develops a polygenic score to adjust PSA levels, improving the detection of aggressive prostate cancer while reducing unnecessary biopsies.

Combining Asian-European Genome-Wide Association Studies of Colorectal Cancer Improves Risk Prediction Across Race and Ethnicity

This study improves polygenic risk scores for colorectal cancer by combining Asian and European ancestry data, enhancing risk prediction across diverse racial and ethnic groups.

Fine-Mapping and Credible Set Construction using a Multipopulation Joint Analysis of Marginal Summary Statistics from Genome-wide Association Studies

This paper introduces mJAM, a multi-population fine-mapping method that improves credible set construction by incorporating population-specific LD structures and demonstrates its effectiveness in real GWAS data.

Inverted genomic regions between reference genome builds in humans impact imputation accuracy and decrease the power of association testing

The paper identifies inverted genomic regions between human reference genome builds that affect imputation accuracy and association testing power, proposing a heuristic to correct these issues.

Causal effects on complex traits are similar across segments of different continental ancestries within admixed individuals

The paper quantifies similarity in causal effects across local ancestries in admixed individuals and finds high genetic correlation (radmix=0.95) within individuals.

Multi-ancestry fine-mapping improves precision to identify causal genes in transcriptome-wide association studies

This paper introduces MA-FOCUS, a multi-ancestry fine-mapping framework that improves the identification of causal genes in TWAS by leveraging ancestry-specific LD and eQTL patterns.

Polygenic Risk Scores for Prediction of Breast Cancer Risk in Women of African Ancestry: a Cross-Ancestry Approach

This paper develops polygenic risk scores for breast cancer prediction in women of African ancestry by combining African and European ancestry datasets, improving prediction accuracy.

Ancestral diversity improves discovery and fine-mapping of genetic loci for anthropometric traits - the Hispanic/Latino Anthropometry Consortium

This study identifies novel genetic loci for BMI, height, and WHRadjBMI in Hispanic/Latino populations and shows the benefits of ancestral diversity in GWAS.

Bayesian Variable Selection with a Pleiotropic Loss Function in Mendelian Randomization

This paper introduces a Bayesian variable selection algorithm for Mendelian randomization that identifies genetic variants with minimal pleiotropy, showing significant risk-increasing effects of blood pressure on coronary heart disease.

Genetic architectures of proximal and distal colorectal cancer are partly distinct

This study identifies 13 new genetic loci specific to proximal or distal colorectal cancer subtypes, revealing partly distinct genetic architectures for these tumor locations.

Genome-wide Association Study of Pediatric Obsessive-Compulsive Traits: Shared Genetic Risk between Traits and Disorder

This study identifies a genome-wide significant variant for OC traits and shows shared genetic risk between OC traits and OCD.

A Hierarchical Approach Using Marginal Summary Statistics for Multiple Intermediates in a Mendelian Randomization or Transcriptome Analysis

This paper introduces hJAM, a hierarchical model that improves causal inference in Mendelian randomization and transcriptome-wide association studies by incorporating prior information and accounting for SNP correlations.

HiLDA: a statistical approach to investigate differences in mutational signatures

HiLDA identifies mutational patterns and their frequencies in cancer data, showing significant associations with mutation timing in colon cancer.

Shared heritability and functional enrichment across six solid cancers

This study quantifies genetic correlations between six solid cancers and other diseases using GWAS data, finding shared heritability and functional enrichment in regulatory regions.

Large-scale transcriptome-wide association study identifies new prostate cancer risk regions

This study integrates a large prostate cancer GWAS with gene expression data to identify 235 genes associated with risk, prioritizing causal genes through Bayesian credible sets.