The first computational tool that enables both unsupervised and supervised discovery of tissue spatial domains

A spatial omics data analysis tool that enables both unsupervised and supervised discovery of complex tissue cellular neighborhoods from cell phenotypes.

Code accompanying our manuscript "Coordinated cellular neighborhoods orchestrate antitumoral immunity at the colorectal cancer invasive front"

Diverse Cluster Ensemble in R

A novel computational method for inferring cell-type-specific signaling networks using single-cell transcriptomics data for better characterization of cell-cell communication.

SpaGCN: Integrating gene expression, spatial location and histology to identify spatial domains and spatially variable genes by graph convolutional network

LIANA: a LIgand-receptor ANalysis frAmework

Survival package for R

an Extremely Fast Approximate Nearest Neighbor graph construction Algorithm framework

Graph Neural Network Library for PyTorch

Must-read papers on network representation learning (NRL) / network embedding (NE)