README

Related to the collection of data and script from Van Maldegem, Valand, et al. 2021


Set the working directory in R to the parent folder that contains all the folders and files needed for input, e.g.:
Working_directory	/3D_plots
			/Figures_input
			/Neighbourhood_analysis
			/Stats_input

Also make an output folder within this same working durectory, where files can be saved:
Working_directory	/output


The order of data processing is:
Segmentation with imcyto
      >input: IMC_ometiff_files & metadata.csv
      >plugins: Segmentation_plugins
normalisation_and_scaling.R
	> Normalisation_input
rPhenograph_clustering.R
	> Clustering_input

To generate the plots in Figure 2 in the paper: 
Code_for_figure_2.R
	>Figure_2_input

Annotation of the clusters is done with Celldata_postprocessing
Celldata_postprocessing.R
      > Figures_input/ input_celldata_postprocessing.csv

To generate the plots in Figure 3-6 in the paper: 
Code_for_figures.R
      > Figures_input/input_celldata_complete.csv
      > Figures_input/macrophage_umap.csv
      > Figures_input/Tcell_umap.csv
Code_for_Suppl_Figures.R
      > Figures_input/input_celldata_complete.csv
neighbouRhood_permutation_prep.R
	> Neighbourhood_analysis/input/É
      > Figures_input/input_celldata_complete.csv
neighbouRhood_permutation_test.R
	> Neighbourhood_input
neighbouRhood_permutation_downstream_analysis.R
      >Neighbourhood_input

Statistics using the linear mixed-modelling are detailed in separate scripts.
lme_counts.R
	> Stats_input/counts_table.csv
	> Stats_input/glmer_full_3c.rds
	> Stats_input/glmer_null_3c.rds
	> Stats_input/glmer_full_3d.rds
	> Stats_input/glmer_null_3d.rds
lme_neighbours.R
      > Stats_input/neighbouRhood_figure4d_lme_input.csv
lme_means_and_distances.R
      > Stats_input/means_table.csv