axelalmet / fibroblastanalysis_2023

Python and R code used to produce the analysis in Almet et al. (2023), "Fibroblasts evolve in single-cell state to drive extracellular matrix and signaling changes across wound healing."

FibroblastAnalysis_2023

Python and R code used to produce the analysis in Almet et al. (2023), "Fibroblasts evolve in single-cell state to drive extracellular matrix and signaling changes across wound healing."

The repository is broken down as follows:

• data contains .csv files of the functional gene sets used to disseminate functional drivers of fibroblast heterogeneity
• code contains the Jupyter notebooks and R scripts used to generate all of the analysis
• output contains the saved .csv files of cell-cell communication activity between fibroblasts and immune cells, as determined by CellChat.

The integrated skin and fibroblast data can be found in the `data' folder of the following Google Drive link:

https://drive.google.com/drive/folders/1vhJHOT6FSlkfmri-vSq2LmoK20_2Uruq?usp=share_link

Upon publication, we will move the data to Zenodo for more accessible sharing.