Jinming Cheng

RankMap improves cell type annotation in spatial and single-cell transcriptomics by using rank-based representations and multinomial regression, achieving competitive accuracy and faster runtime.

Binning transcript and cell coordinates into spatial vectors lets jazzPanda call smaller, spatially concordant marker sets than Wilcoxon or t-tests on Xenium/CosMx data, while modelling replicates and negative-control background.

hoodscanR identifies and analyzes cell neighborhoods in spatial transcriptomics data, revealing transcriptional differences in tumor cells across neighborhoods.

SpNeigh analyzes spatial transcriptomics data to detect neighborhood effects and differential expression, revealing tissue interface populations and spatial gene patterns in mouse brain, human breast cancer, and liver.

The paper demonstrates a workflow for trajectory inference and time course analysis of scRNA-seq data from mouse mammary gland, identifying genes associated with pseudotime.