Yun Li

A connection-level genetic atlas of human cortical functional connectivity at rest and during a task

The paper presents a connection-level genetic atlas of human cortical functional connectivity, identifying genetic loci associated with resting and task states.

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.

Computation and resource efficient genome-wide association analysis for large-scale imaging studies

This paper introduces RVGA, a framework for efficient genome-wide association analysis in imaging genetics, identifying novel loci and genetic correlations in brain structures using UK Biobank data.

Trans-eQTLs reveal the architecture of human gene regulatory networks

The paper maps cis- and trans-eQTLs in blood samples to infer gene regulatory networks and prioritize trait-relevant pathways.

Functional Annotation of the Major Histocompatibility Complex Locus

This study identifies hundreds of new cis-regulatory element-gene connections in the MHC locus using CRISPR screens and single-cell transcriptomics, revealing cell type-specific regulatory mechanisms.

An integrated view of the structure and function of the human 4D nucleome

The paper integrates 4D Nucleome data to analyze 3D genome structure and function in human cells, revealing chromatin domains, loops, and interactions, and showing how genetic variants affect genome folding.

Accurate and robust 3D genome feature discovery from multiplexed DNA FISH

ArcFISH identifies 3D genome features from multiplexed DNA FISH data by modeling axis-specific measurement errors, showing reliable detection of chromatin loops, TAD boundaries, and A/B compartments.

Hi-C informed kernel association test: integrating 3-dimensional genome structure into variant-set association for whole-genome sequencing data

The paper introduces a Hi-C informed kernel association test to integrate 3D genome structure into variant-set association analysis for WGS data, showing improved detection of rare-variant sets.

Ancestry Calibration of Polygenic Risk Scores Improves Risk Stratification and Effect Estimation in African American Adults

This study calibrates polygenic risk scores (PRS) for African American adults based on genetic ancestry, improving risk stratification and effect estimation for type 2 diabetes and height.

SnapHiC-G: identifying long-range enhancer-promoter interactions from single-cell Hi-C data via a global background model

SnapHiC-G identifies long-range enhancer-promoter interactions from scHi-C data using a global background model, showing high sensitivity and cell-type-specific enrichment of neuropsychiatric disease SNPs.

MAST-Decon: Smooth Cell-type Deconvolution Method for Spatial Transcriptomics Data

MAST-Decon improves spatial transcriptomics deconvolution by incorporating spatial neighborhood and histological image features to enhance accuracy and reliability.

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.

Genetic polymorphisms of Leukocyte Immunoglobulin-Like Receptor B3 (LILRB3) gene in African American kidney transplant recipients are associated with post-transplant graft failure

The paper identifies four SNPs in the LILRB3 gene associated with graft failure in African American kidney transplant recipients and links them to immune-related diseases.

SnapFISH-IMPUTE: an imputation method for multiplexed DNA FISH data

SnapFISH-IMPUTE imputes missing values in multiplexed DNA FISH data, improving downstream analysis by preserving pairwise distances and enhancing clustering and enhancer-promoter loop detection.

High throughput PRIME editing screens identify functional DNA variants in the human genome

This paper introduces PRIME, a high-throughput prime editing screen that identifies functional DNA variants in the human genome with base-pair resolution.

Functional characterization of gene regulatory elements and neuropsychiatric disease-associated risk loci in iPSCs and iPSC-derived neurons

The paper identifies functional CREs in iPSCs and neurons and links them to neuropsychiatric disease risk variants.

The pivotal role of the X-chromosome in the genetic architecture of the human brain

The paper investigates the genetic impact of the X-chromosome and sex differences in the human brain, identifying 72 genome-wide significant trait-locus pairs linked to brain-related disorders.

SnapFISH: a computational pipeline to identify chromatin loops from multiplexed DNA FISH data

SnapFISH identifies chromatin loops from multiplexed DNA FISH data with high sensitivity and accuracy in mouse embryonic stem cells.

Title: Leveraging Base Pair Mammalian Constraint to Understand Genetic Variation and Human Disease

The paper uses evolutionary constraint scores to identify functional genomic regions and finds they are enriched for variants associated with common diseases.

DeepGWAS: Enhance GWAS Signals for Neuropsychiatric Disorders via Deep Neural Network

DeepGWAS enhances GWAS signals for neuropsychiatric disorders using deep neural networks, improving locus detection in schizophrenia and validating results in other disorders.

Cell composition inference and identification of layer-specific spatial transcriptional profiles with POLARIS

POLARIS infers cell composition from histology images and identifies layer-specific differentially expressed genes in spatial transcriptomics data.

Uncovering Cross-Cohort Molecular Features with Multi-Omics Integration Analysis

This paper improves multi-omics integration by enhancing orthogonality in canonical vectors and demonstrates transferability across cohorts for proteomics and methylomics data.

Mosaic chromosomal alterations in blood across ancestries via whole-genome sequencing

This study uses whole-genome sequencing to analyze mosaic chromosomal alterations across diverse ancestries, finding higher rates in certain populations and associations with germline variants.

S-BEAM: A Semi-Supervised Ensemble Approach to Rank Potential Causal Variants and Their Target Genes in Microglia for Alzheimer's Disease

This study introduces S-BEAM, a semi-supervised ensemble method to prioritize non-coding variants and their target genes in microglia for Alzheimer's disease, identifying 11 risk variants and proposing 37 for further study.

Improving polygenic risk prediction in admixed populations by explicitly modeling ancestral-specific effects via GAUDI

GAUDI improves polygenic risk prediction in admixed populations by modeling ancestry-specific and shared effects, outperforming existing methods in simulations and real data.

Genetic influences on the shape of brain ventricular and subcortical structures

The paper identifies 60 genetic loci associated with brain ventricular and subcortical shape features using shape measures from over 45,000 UK Biobank and ABCD study subjects.

SnapHiC-D: a computational pipeline to identify differential chromatin contacts from single cell Hi-C data

SnapHiC-D identifies differential chromatin contacts between two scHi-C datasets with high sensitivity and accuracy, showing correlation with cell-type-specific gene expression and epigenomic features.

A comprehensive comparison on cell type composition inference for spatial transcriptomics data

This paper compares eight ST deconvolution methods using four real datasets to evaluate their performance in inferring cell type composition from spatial transcriptomics data.

Common variants contribute to intrinsic human brain functional networks

This study identifies common genetic variants influencing intrinsic brain networks using rsfMRI data from 44,190 individuals, finding associations with cognitive and clinical traits.

A computational method for Cell type-specific Expression Quantitative Trait Loci mapping using bulk RNA-seq data

This paper introduces a statistical method to map cell type-specific eQTLs using bulk RNA-seq data, improving accuracy over existing methods by leveraging allele-specific expression.