candidate_genes

A survival analysis of cancer patients using a Kaplan Meier estimator based on co-expression of modifier genes with either a tumor suppressor gene or oncogene. This code includes a GUI for an easier run.

Tutotrials can be found here:

https://www.youtube.com/watch?v=rqeOjp93ZNs&list=PLjhAI0VKQp-PPPpFLUs6dYqPODt_rLG2d&ab_channel=toturials_for_my_github_codes

p-value

The way the p-value was calculated is by log-rank test. Documentation of the way Chi2 was calculated can be found in this file:

• Kaplan_Meier_Analysis.pdf

And is based on this book: Kleinbaum, D. G. (1998). Survival analysis, a self‐learning text. pg. 82.

The method for the Kaplan Meier calculation needs to be downloaded separately from: https://www.mathworks.com/matlabcentral/fileexchange/64582-matsurv

Creed, Jordan, et al. “MatSurv: Survival Analysis and Visualization in MATLAB.” Journal of Open Source Software, vol. 5, no. 46, The Open Journal, Feb. 2020, p. 1830, doi:10.21105/joss.01830.

For future coders

Main code to start working with -

• Candidate_Genes.m

Code for the GUI -

• canddiate_genes3.mlapp (exported to candidateGenesGUI.m)

Ignore -

• candidate_genes.mlapp
• candidate_genes2.mlapp
• create_gene_expression_table.py

Fix -

• mutation_analysis.m
• cancer_subtypes_analysis.m