Early detection and diagnosis of cancer with interpretable machine learning to uncover cancer-specific DNA methylation patterns

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This is the code repo for EMethylNet. We create XGBoost models that can classify 13 cancer types as well as non-cancer tissue samples using DNA methylome data. We utilise the features identified by the multiclass XGBoost model to develop EMethylNET (Explainable Methylome Neural network for Evaluation of Tumours), a multiclass deep neural network. We then run analyses on the features detected by the XGBoost models.

Folder structure:

1. First start with data_preprocessing/. This will download the TCGA data and pre-process it into csv files.

2. Now train some models:

   • Start with simple_methods/ (logistic regression and SVM)
   • Then run xgboost/ models
   • Finally, make a neural network in FoundFeatureNN/

3. Analyse the models' features:

   • Map the features to genes in mapping_to_genes/
   • Run gene ontology analysis in biology/gProfiler/
   • Look at literature evidence in biology/pangaea/
   • Analyse enriched pathways in biology/pathways/
   • Analyse the multiclass lncRNAs in biology/lncRNAs/
   • Run survival analysis in survival_analysis/

Code for each figure

• Figure 2:
  • 2a+b: xgboost/create_classifiers.ipynb
  • 2c+d: xgboost/create_classifiers.ipynb and xgboost/binary_xgboost_performance.ipynb
  • 2e: xgboost/create_classifiers.ipynb
  • 2f+g: xgboost/multiclass_xgboost_performance.ipynb
• Figure 3:
  • 3a+b+d+e: xgboost/binary_xgboost_external_performance.ipynb
  • 3c: xgboost/binary_xgboost_external_COAD_cm.ipynb
• Figure 4:
  • 4b,c,d: FoundFeatureNN/multiclass_DNN_external_performance.ipynb
• Figure 5:
  • 5a: biology/gProfiler/REVIGO_smaller.r
  • 5b: biology/pangaea/analysing_pangea_results.ipynb
  • 5c: biology/pathways/KEGGPathwayAnalysis.Rmd
  • 5d: biology/pathways/visualising_enriched_kegg_pathways/visualising_enriched_kegg_pathways.ipynb
• Figure 6:
  • Hand curated networks in pathviso and cytoscape
• Figure 7:
  • 7a: biology/lncRNAs/proportions_of_lncRNAs/gene_stats.Rmd
  • 7b+c: biology/lncRNAs/combining_databases_and_pangea.ipynb
  • 7d: biology/lncRNAs/validate_with_properties/CLC_comparison_results.Rmd
  • 7e: biology/lncRNAs/validate_with_properties/CLC_comparison.Rmd
• Figure 8:
  • 8a: survival_analysis/SurvivalAnalysisNoTestset.Rmd
  • 8b+c: survival_analysis/SurvivalAnalysis.Rmd

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