Spatial analysis of cell clusters

In order to quantify spatial clustering of cell types, neurons in ISH images (for humans, one male, one female and for mice several sections from different DRGs and animals) were manually outlined and annotated as NEFH-only or SCN10A-only; cells expressing both genes were not counted. Centroid coordinates of these cells and their distances were analyzed in Python 3.7. The nearest neighbors were identified based on Euclidean distance (Scikit-Learn package) and the percentage of NEFH and SCN10A cells in each neighborhood of size 1–40 cells was calculated. Statistical significance between NEFH- and SCN10A-surrounding neighborhoods was determined using a one-tailed Mann–Whitney U-test (Scipy Stats package).

The specific code for the spatial cluster analysis has been made available as a Jupyter Notebook at https://gist.github.com/lars-von-buchholtz/de95a8874bb06dd47faf6dcacc0f411d

A PDF copy of the Notebook is attached to this protocol.

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