Investigating Dual-Targeting of FAK and STING for Modulating the Tumor Immune Microenvironment Using an In Vitro NK-92 Model and TCGA Transcriptome Data.
This repo contains the code used for analysis of The Cancer Genome Atlas (TCGA) and CIBERSORT data for PTK2 and STING1 differential expression.
The TCGA datasets imported are sorted into two subgroups:
- PTK2-high / STING1-low
- PTK2-low / STING1-high
The Jupyter Notebook file requires the TCGA COAD and READ datasets and the CIBERSORT dataset to be downloaded locally.
The TCGA datasets can be found here: https://portal.gdc.cancer.gov/analysis_page?app=Downloads
Filter by:
Data Category: Transcriptome Profiling
and
Data Type: Gene Expression Quantification
The CIBERSORT dataset can be found here: https://gdc.cancer.gov/about-data/publications/panimmune
Use the file here: CIBERSORT immune fractions - TCGA.Kallisto.fullIDs.cibersort.relative.tsv
TCGA Acknowledgement: The results shown here are in whole or part based upon data generated by the TCGA Research Network: https://www.cancer.gov/tcga.
CIBERSORT citation: Newman AM, Steen CB, Liu CL, Gentles AJ, Chaudhuri AA, Scherer F, et al. Determining cell type abundance and expression from bulk tissues with digital cytometry. Nature Biotechnology. 2019 Jul 1;37(7):773–82. doi:10.1038/s41587-019-0114-2