This repository contains the code for genetic analysis, matching and survival analysis for
Microbubble-enhanced focused ultrasound and temozolomide for high-grade gliomas: safety, feasibility, efficacy, and sono-liquid biomarker analyses.
The project is divided into two main branches:
- Trajectory Figures (genetic analysis)
- Matching and Survival Analysis
Run the R file named c-score to obtain the two groups of outcome of interest for cfDNA (EP and LTS).
Run the R file named f-score to obtain the two groups of outcome of interest for FLRatio (EP and LTS).
Run the R file named all in one plot to generate the trajectory plot for all four groups.
Run the R file named peak vs last and time trend for cfdna to generate the last observed box plot for cfDNA, including active tumors, early progressors, and long-term survivors.
Run the R file named peak vs last and time trend for fragment to generate the last observed box plot for FLratio, including active tumors, early progressors, and long-term survivors.
This section contains data and code necessary to perform coarsened exact matching and survival analysis.
- Patient datasheet:
data/FinalData.csv
-
Matching Analysis Run
code/matchingCEM.rto generate:data/MatchedData.csv: Final matched data sheetresults/CEM_baseline.txt: Summary of balance for unmatched dataresults/CEM_summary.txt: Summary of balance for matched dataresults/matching_check.png: Comparison density plot of variables pre- and post-matching
-
Survival Analysis Run
code/survivalAnalysis.rto generate:results/PFS_curves.svg: Plot of Kaplan-Meier PFS curvesresults/OS_curves.svg: Plot of Kaplan-Meier OS curvesresults/PFS COX survival curve.svg: Plot of Cox-adjusted PFS curvesresults/OS COX survival curve.svg: Plot of Cox-adjusted OS curvesresults/cox_results.txt: Cox proportional hazards regression results, including proportional hazards assumption test results
-
Sensitivity Analysis Run
code/sensitivityAnalysis.rto generate:results/sensitivity_analysis_OS.txt: Results of sensitivity analyses for OSresults/sensitivity_analysis_PFS.txt: Results of sensitivity analyses for PFS
- Clone this repository
- Install the required R packages
- Run the R scripts in the order specified above
If you use this code or data in your research, please cite our paper:
[Citation details to be added upon publication]
[Specify the license under which this project is released]
For any questions or issues, please open an issue in this repository or contact Jeremi Chabros [jchabros@hsph.harvard.edu].