Penghui Yang

De novo analysis of bulk RNA-seq data at spatially resolved single-cell resolution

Bulk2Space deconvolves bulk RNA-seq data to reveal spatial and cellular heterogeneity using single-cell and spatial transcriptomics references, identifying immune cell spatial variance and novel gene patterns in mouse brain regions.

Knowledge-graph-based cell-cell communication inference for spatially resolved transcriptomic data with SpaTalk

SpaTalk infers cell-cell communication from spatial transcriptomic data using a knowledge graph and graph network, outperforming existing methods on public datasets and revealing insights into tissue communication mechanisms.

Reconstruction of the cell pseudo-space from single-cell RNA sequencing data with scSpace

scSpace reconstructs a pseudo-space from single-cell RNA-seq data to identify spatially variable cell subclusters and their biological relevance.

Single-cell analysis reveals a pathogenic cellular module associated with early allograft dysfunction after liver transplantation

The paper constructs a single-cell transcriptomic atlas of transplanted livers and identifies an EAD-associated pathogenic cellular module.

Reference-free Cell-type Annotation for Single-cell Transcriptomics using Deep Learning with a Weighted Graph Neural Network

scDeepSort is a reference-free cell-type annotation tool for scRNA-seq data that outperforms reference-dependent methods in accuracy across human and mouse datasets.