Table 1.
A selection of open-source software packages for statistical analysis of cell images
| Package | Capability | Year | Reference |
|---|---|---|---|
| Squidpy | spatial graphing, neighborhood proximity tests, spatial autocorrelation tests | 2022 | https://pypi.org/project/squidpy/30 |
| Giotto | spatial correlation, spatial domain detection, pattern simulation | 2021 | https://rubd.github.io/Giotto_site/31 |
| ImaCytE | interactive visual analysis of cell microenvironment | 2021 | https://github.com/biovault/ImaCytE32 |
| Spark | spatial regression using generalized linear spatial models (GLSMs) | 2020 | https://xzhoulab.github.io/SPARK/33 |
| SpatialDE | Gaussian process regression | 2018 | https://github.com/Teichlab/SpatialDE34 |
| histoCAT | neighborhood analysis: permutation test of local interaction pairs compared with random distributions | 2017 | https://bodenmillergroup.github.io/histoCAT/35 |
For an extensive list of available software see https://htmlpreview.github.io/?https://github.com/drieslab/awesome-spatial-data-analysis/blob/main/review_spat_trns_methods.html.