Spatial Random Effects Clustering of Single Cell Data
Description
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'.