Wenfei Jin

Garfield integrates single-cell and spatial multi-omics data into a shared space, outperforming existing methods in identifying spatial niches and revealing immune microenvironment heterogeneity.

CNVPipe improves CNV detection in WGS by integrating CNV tools with machine learning, reducing FDR and increasing sensitivity for both bulk and single-cell data.

The paper identifies two distinct categories of differentially expressed genes in tumor subclones based on their regulatory and functional characteristics using single-cell transcriptomic and genomic data from colorectal cancer patients.

The paper profiles chromatin accessibility dynamics in zebrafish embryos using single-cell ATAC-seq to identify enhancers and transcription factor motifs involved in early cell fate decisions.

The paper integrates single-cell RNA-seq data from multiple tissues to construct a cell atlas of hematopoietic stem and progenitor cells (HSPCs) and identifies migration patterns and signaling interactions involved in their cross-tissue differentiation.

This study develops scPolyA-seq to analyze alternative polyadenylation at single cell resolution, finding that many genes use only one polyA site per cell and identifying cell cycle-related polyA site usage switches.

ISSAAC-seq jointly profiles chromatin accessibility and gene expression in single nuclei, revealing cell types, regulatory elements, and chromatin dynamics in mouse cerebral cortex.

This study uses single-cell RNA sequencing to analyze pediatric ependymoma subclonal heterogeneity and identifies gene expression patterns linked to patient survival.

The paper identifies MSC subpopulations and their differential responses to inductions using single-cell RNA-seq, revealing subtype-specific gene expression and differentiation potential.

The paper re-analyzes T cell subsets using scRNA-seq, identifies new subpopulations, and shows that gene expression patterns define more homogeneous cell populations than surface markers.

scGAE is a dimensionality reduction method for scRNA-seq data that preserves topological structure, outperforming existing methods in trajectory reconstruction and clustering.

The paper introduces k-mer substring space decomposition (kssd), a sequence sketching technique that improves resemblance and containment analysis for large-scale omics data by being more accurate and efficient than existing methods.

The paper constructs a single-cell atlas of hematopoiesis and leukemogenesis, identifies leukemia subpopulations, and develops a composite index to predict clinical outcomes.

The paper uses multi-omic data from hybrid mice to reveal symmetrical positioning of homologous chromosomes in the 3D nucleus and epigenetic regulation differences between B6 and Cast strains.

The paper investigates how CTCF knockdown affects genome-wide cell-to-cell variation using single-cell RNA-seq, finding increased expression noise and enrichment of transcription factor-related genes in CTCF-KD cells.

This study identifies accumulated transcriptional regulation degeneration as a key contributor to Alzheimer's disease progression and clinical outcomes.