CytoMAP makes advanced data analytic techniques accessible for cell position and phenotype data. The goal is to take established analytical techniques, such as neural network based clustering algorithms, and package them in a user friendly way, allowing researchers to use them to explore complex cellular datasets.
Read about version changes on https://cstoltzfus.com/news
For descriptions of functions see https://gitlab.com/gernerlab/cytomap/-/wikis/home
If you run into bugs, or have questions about features; post a question on the Scientific Community Image Forum at: https://forum.image.sc/
Be sure to add the cytomap tag to your topic for visibility.
Stoltzfus, Caleb R., et al. “CytoMAP: A Spatial Analysis Toolbox Reveals Features of Myeloid Cell Organization in Lymphoid Tissues.” Cell Reports, vol. 31, no. 3, Elsevier BV, Apr. 2020, p. 107523, doi:10.1016/j.celrep.2020.107523.
Inspired by: fca_readfcs, PeterBeemiller/ImarisReader, Uniform Manifold Approximation and Projection (UMAP)
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