SpaIm is a tool for de-noising gene expressions in the spatial transcriptomics (ST) data. All the copyrights are explained by Kenong Su kenong.su@pennmedicine.upenn.edu from Dr. Li's lab.
Using Dirichlet Multinomial (DM) Mixture Models for simulation the downsampled gene expression data. The DM parameters are estimated by simple method of moments (MoM) approach. It includes two steps: draw from the Dirichlet distribution, and simulate multinomial distribution with a shrinked N. The shrinked sequence depth N can be draw from the gamma distribution. The example can be found here DM_simulation_Rmd or DM_simulation_html, and the breast cancer 10x Visium data can be found here IDC. The corresponding compiled .h5ad format data can be found at the google drive.
Using NB decoder to de-noise the original gene expression matrix. The workflow includes two inputs followed by the negative bionomial decoder.
The tutorial for running spaIm can be found here