**This project proposed a computational pipeline to analyze the tumor microenvironment in patients with non-small cell lung cancer (NSCLC) using archival pathological samples and multiplexed immunofluorescence.
The computational pipeline was developed on the following operating system:
- Windows 10 Pro.
- Processor: 12th Gen Intel(R) Core(TM) i7-12700K 3.61 GHz
- 32GB RAM
- 64-bit operating system, x64-based processor.
The computational pipeline was developed using the following softwares:
- R version 4.2.0.
- Rstudio Desktop version 1.4.
- Pycharm Python IDE version 2022.12.0.
- R packages listed at the beginning of each R script.
- BioRender
To install the pipeline, simply download the codes and run from local R compiler.
- Installation time all dependencies should take no longer than 30 minutes.
- Codes can be readily used upon downloading and do not require extra installations.
The pipeline consists of five components:
- DataPreparation.R (Read single-cell data for each core and combine as one, compute cell densities by core, read cell boundaries data)
- NSCLC_Pipeline1.R (First-order characterizations, tSNE plot, population fractions comparison and clustering, survival analysis, patient stratification)
- NSCLC_Pipeline2.R (Cell density comparison betweeen survival group, Shannon's entropy, ratios, )
- NSCLC_Pipeline3.R (Network analysis, minimum spanning tree, pairwise Gcross function, voronoi tesselation)
- NSCLC_Pipeline4.R (RiskScale)
- NSCLC_Pipeline5.R (PD-1/PD-L1 statistics)
- NSCLC_Pipeline6.R (Analysis on validation cohort)
- Function.R (Custom R functions defined for computations)
Distributed under the MIT License. See LICENSE for more information.
Haoyang Mi - hmi1@jhmi.edu