Jin Jin

Constructing a Literature-Derived Database for Benchmarking Polygenic Risk Score Construction Methods with Spectral Ranking Inferences

This study constructs a literature-derived database to benchmark polygenic risk score methods using spectral ranking, identifying top and bottom performers and providing phenotype-specific insights.

Reconstructing multi-scale tissue spatial architecture from single-cell RNA-seq with REMAP

REMAP reconstructs spatial tissue architecture from scRNA-seq using deep learning and ST references, revealing microenvironmental features and cancer subtypes.

PennPRS: a centralized cloud computing platform for efficient polygenic risk score training in precision medicine

PennPRS provides a cloud platform for training polygenic risk scores without individual-level data, validated with simulations and real data across 6,000 phenotypes.

Identifying Effect Modification of Latent Population Characteristics on Risk Factors with a Sparse Varying Coefficient Regression

The paper introduces a sparse varying coefficient regression model to capture effect modification by latent features in risk factor-disease outcome associations, showing improved performance in lung cancer stage prediction.

One score to rule them all: regularized ensemble polygenic risk prediction with GWAS summary statistics

This paper introduces a statistical framework for regularized ensemble polygenic risk prediction using GWAS summary statistics, showing improved performance across traits and populations.

Bayesian Mendelian Randomization Analysis for Latent Exposures Leveraging GWAS Summary Statistics for Traits Co-Regulated by the Exposures

This paper introduces a Bayesian Mendelian randomization framework to analyze causal effects of latent exposures on disease outcomes using GWAS summary statistics for co-regulated traits.

A Graph Informed Framework Empowering Gene Pathway Discovery and Gene Expression-Assisted Disease Classification

This paper introduces a graph-informed framework that improves gene pathway analysis and disease classification by integrating gene regulatory networks into statistical methods, showing better performance in simulations and a lung cancer dataset.

An Ensemble Penalized Regression Method for Multi-ancestry Polygenic Risk Prediction

This paper introduces PROSPER, an ensemble penalized regression method for multi-ancestry polygenic risk prediction, showing improved performance across diverse populations.

MUSSEL: Enhanced Bayesian Polygenic Risk Prediction Leveraging Information across Multiple Ancestry Groups

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

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.

Mendelian Randomization Analysis Using Multiple Biomarkers of an Underlying Common Exposure

This paper introduces MRLE, a method for Mendelian Randomization analysis of latent exposures using multiple biomarkers, showing improved power and evidence for inflammation's causal role in diseases.

A new method for multi-ancestry polygenic prediction improves performance across diverse populations

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.

A Polygenic Score for Reduced Kidney Function and Adverse Outcomes in a Chronic Kidney Disease Cohort

The paper assesses if a polygenic score for reduced kidney function predicts adverse outcomes in chronic kidney disease patients, finding significant associations but no improvement in prediction over existing risk equations.

Polygenic Risk Scores for Kidney Function to the Circulating Proteome, and Incident Kidney Diseases: the Atherosclerosis Risk in Communities Study

This study develops a polygenic risk score for eGFR and shows its association with kidney disease outcomes and plasma proteins in the ARIC study.