BayXenSmooth - Smooth and Spatial Bayesian Clustering for Xenium Data
A hierarchical approximate Bayesian model for expression data generated by 10X's Xenium platform. Provides convergent posterior uncertainty quantification of cluster assignments for a wide variety of expression tabulated data.
Dec 31, 2024
A Graph Convolutional Network for Spatial Transcriptomics Modelling
A spatially informed GCN tailored for spatial transcriptomics data. Incorporating expression information from neighboring cells is an open problem and we attempt to leverage deep graph convolutional networks to maximize response expression likelihoods.
Sep 30, 2023