Yun Li

The paper integrates chromatin architecture with transcriptomic data to explore cell-type-specific gene regulatory networks in brain disorders, identifying distinct cellular contributions to Alzheimer's and psychiatric diseases.

SMNN improves batch effect correction in scRNA-seq by using supervised mutual nearest neighbor detection within cell types, leading to better merging and retention of cell-type specific features.

This study uses TOPMed whole genome sequences to improve imputation quality and detect rare variant associations in admixed African and Hispanic/Latino populations, identifying two novel associations with hematological traits.

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

This study performs transcriptome-wide association analysis on 211 neuroimaging traits, identifies 204 genes, and shows TWAS-derived polygenic risk scores explain up to 6.97% of phenotypic variance.

This study identifies 287 novel genetic variants associated with brain volumes using GWAS in 19,629 UK Biobank participants and finds genetic correlations with cognitive and mental health traits.

SAME-clustering improves single-cell RNA-seq clustering by combining multiple methods to produce a more accurate and diverse ensemble solution.

The paper develops an improved Hi-C protocol and bias-correction pipeline to map chromatin loops in human neurogenesis and brain tissues, showing their role in neural differentiation and GWAS gene identification.

The paper identifies cis-regulatory chromatin contacts in neural cells and links them to genetic variants associated with complex neurological disorders.

The paper introduces SMUT, a method to test mediation effects of multiple SNPs on phenotypes, showing improved power and identifying known mediators in a real dataset.

MAPS processes PLAC-seq and HiChIP data to identify long-range chromatin interactions by removing biases and analyzing contact frequencies.

SAFE-clustering integrates multiple clustering methods to improve accuracy and robustness in scRNA-seq data analysis, reducing cluster deviation and improving assignment compared to individual methods.

The paper examines the heritability of regional brain volumes using genetic and neuroimaging data from multiple cohorts, finding high heritability and consistent patterns across populations.

Genome-wide association meta-analysis of 130,664 major depression cases and 330,470 controls identifies 44 independent risk loci enriched in cortical neurons, conserved mammalian regions, splicing networks, and antidepressant targets.

The paper develops a tool for fast and accurate reconstruction of neuronal populations in large brain datasets, achieving results close to ground truth with high automation.

This study identifies genetic variants associated with epigenetic age acceleration and shows TERT's role in regulating the DNA methylation clock.

HUGIn is a web browser for visualizing Hi-C data from 21 human primary tissues and cell lines to assess chromatin contacts across and specific to tissues or cell lines.