scSpatialSIM

Single cell resolution data has been valuable in learning about tissue microenvironments and interactions between cells or spots. This package allows for the simulation of this level of data, be it single cell or ‘spots’, in both a univariate (single metric or cell type) and bivariate (2 or more metrics or cell types) ways. As more technologies come to marker, more methods will be developed to derive spatial metrics from the data which will require a way to benchmark methods against each other. Additionally, as the field currently stands, there is not a gold standard method to be compared against. We set out to develop an R package that will allow users to simulate point patterns that can be biologically informed from different tissue domains, holes, and varying degrees of clustering/colocalization. The data can be exported as spatial files and a summary file (like 'HALO'). https://github.com/FridleyLab/scSpatialSIM/.

Last 30 days

This package has been downloaded 184 times in the last 30 days. More than a random curiosity, but not quite a blockbuster. Still, it's gaining traction! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 8 times.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Last 365 days

This package has been downloaded 2,195 times in the last 365 days. Now we’re talking! This work is officially 'heard of in academic circles', just like those wild research papers on synthetic bananas. The day with the most downloads was Oct 02, 2024 with 56 downloads.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.