Weifang Liu

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.

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

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

The paper improves genotype imputation for CF patients using the TOPMed reference panel and a CF-specific imputation panel, enhancing marker coverage and PRS accuracy.

MUNIn identifies long-range chromatin interactions across multiple samples by accounting for sequencing depth and heterogeneity, achieving lower false positives and higher power for shared peaks.

The paper identifies placental gene-trait associations across the life course using multi-omics data, finding genetic effects on early-life traits but not later ones.

This study characterizes 3D epigenomic landscapes during human corticogenesis, revealing chromatin looping and super interactive promoters involved in lineage-specific gene regulation.