IFNγ cancer project

R and Matlab codes used for the analysis performed in the paper "Bystander IFNγ activity promotes widespread and sustained cytokine signaling altering the tumor microenvironment".

Recommendations

Before running any of the R scripts please install the following R libraries :

• Pagoda2 (https://github.com/hms-dbmi/pagoda2/tree/master/R)
• fifer (https://github.com/dustinfife/fifer)
• uwot (https://github.com/jlmelville/uwot)
• igraph (https://igraph.org/r/)
• ggplot2 (https://ggplot2.tidyverse.org)
• DESeq2 (https://bioconductor.org/packages/release/bioc/html/DESeq2.html)
• FactoMineR (https://cran.r-project.org/web/packages/FactoMineR/index.html)
• pheatmap (https://cran.r-project.org/web/packages/pheatmap/index.html)

Concerning the Matlab® scripts, please use at least Matlab 2017 and have the Image Processing Toolbox available.

List of the scripts

Each script corresponds to a specific part of the paper :

• In_vitro_RNAseq_analysis.R : R script used to analyze the RNAseq data generated from B cell lymphoma cell line stimulated by IFNγ during various time.
• Melanoma_data_analysis.R : R script used to re-analyze the melanoma MARS-seq data from Li et al. using Pagoda2 pipeline.
• HNSCC_data_analysis.R : R script use to re-analyze the Head and Neck Squamous Cell Carcinoma from Puram et al. using Pagoda2 pipeline.
• Visualize_Image_analysis.R : R script that gathers results of image analysis performed by Matlab and create the figures used in the paper.
• Microscopy_Image_analysis_main.m : Matlab script that performs co-localisation analysis between STAT1-GFP and nuclear mCherry signal both for in-vitro and intra-vital images shown in the main figures. A detailed description of the image processing pipeline is available in as a supplementary figure of the paper.
• Microscopy_Image_analysis_sup.m : Matlab script that performs co-localisation analysis between STAT1-GFP and nuclear mCherry signal for intra-vital images shown in supplementary figures.
• Kinetic_analysis.m: Matlab script used to perform the co-localisation analysis of IFNγ in-vitro stimulated cells across different times.
• LoadImage.m : Basic Matlab script that loads multiple-stack .tiff files into Matlab.
• Pre_processing.m : Basic Matlab script used to clean images before the analysis (background removal, intensity adjustment).
• Nuclei_identification.m : Matlab script used to segment cells through image binarisation and watershed transform.