Immunoproteasome

Analysis of constitutive and Immunoproteasome expression level in solid tumors

Make the following directories in your current path to run the R scripts and notebooks

mkdir data
mkdir plots
mkdir supplementary_tables
mkdir data/tcga_tumor
mkdir data/gtex_normal
mkdir data/r_input
mkdir data/r_output
mkdir data/r_input/gene_exp
mkdir data/time_course

Notebook details

Run the notebooks and R scripts in the following order

1. Exploring_proteasome_expression_pan_cancer

2. immune_cells_gsva.R

3. pathways_gsva.R

4. epi_mes_gsva.R

5. Differential_immune_cells_enrichment

6. Differential_pathways_analysis.ipynb

7. EMT_correlation_analysis.ipynb

8. Copy_no_alteration_mutation_analysis.ipynb

9. Survival_analysis_IP_CP.ipynb

10. TNF_alpha_TGFB1_inducing_proteasome_expr_analysis.ipynb

11. Methylation_and_upstream_pathways_IP_analysis.ipynb

12. Single_cell_preprocess_1.ipynb

13. Single-plots.ipynb

14. Immunotherapy.ipynb

./data contains all the input data for the analysis. tcga tumor gene expression data, GTEx normal gene expression data, tumor mutation burden, TCGA purity data,

./plots contains all the plots generated and provided in the figure

./supplementart_tables contains all the result

./data/tcga_tumor contains the TCGA gene expression data

./data/gtex_normal contains the GTEx gene expression data downloaded from https://toil-xena-hub.s3.us-east-1.amazonaws.com/download/gtex_RSEM_Hugo_norm_count.gz

./data/r_input contains the input data for computing gsva score

./data/r_output contains the resulting gsva scroe and differential enrichment score for immune cells and pathways

./data/r_input/gene_exp contains the gene expression from tcga to run the r script

./data/time_course contains the time course gene expression data which can be downloaded from here [https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE147405]

Required data

All the data used in the analysis has been hosted at [ https://drive.google.com/file/d/19O1GoUpyFRRz0rhs8Ee3Rflm-k3GHkGI/view?usp=share_link ]. Please download the data, unzip it and put it in the data folder as mentioned below.
put all the data file from tcga_tumor folder to ./data/tcga_tumor directory.
put the gene signature file Epithelial_Mesenchymal_gene_list.csv, hall_mark_genes_df.csv, immune_and_pathways_gene_list.xlsx  to ./data/r_input directory.
leave the rest of the files in the ./data directory

Download the additonal GTEx normal gene expression data from  https://toil-xena-hub.s3.us-east-1.amazonaws.com/download/gtex_RSEM_Hugo_norm_count.gz  and put it in the ./data/gtex_normal directory.
Download the time course data from https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE147405  and put it in the ./data/time_course directory

Required packages

Python 3.6.8

jupyter-notebook              5.7.11
matplotlib                    3.0.3
numpy                         1.16.3
seaborn                       0.9.0
scipy                         1.5.4
scanpy                        1.4.4
pandas                        0.25.0
statannot                     0.2.3
anndata                       0.6.22
lifelines                     0.26.3

R version 3.6.3

GSVA                          1.32.0
limma                         3.40.6
preprocessCore                1.46.0
GSEABase                      1.46.0
Biobase                       2.44.0
genefilter                    1.66.0
RColorBrewer                  1.1.3
readxl                        1.4.0