Spatial Random Effects Clustering of Single Cell Data

Allows for identification of cell sub-populations within tissue samples using Bayesian multivariate mixture models with spatial random effects to account for a wide range of spatial gene expression patterns, as described in Allen et. al, 2021 . Bayesian inference is conducted using efficient Gibbs sampling implemented using 'Rcpp'.