Welcome to Comprior’s documentation!

Contents:

• Installation and Usage
  • Install and Run Comprior from Source
    • 1. Installation
    • 2. Usage
  • Run Comprior in a Docker Container
  • Installing Java JDK and Maven on Ubuntu
  • Troubleshooting
• Example Use Cases
  • Breast Cancer
    • Execution via Source Installation
    • Execution via Docker Image
  • Glioma
    • Execution via Source Installation
    • Execution via Docker Image
  • Output Generated by Comprior
    • Detailed Processing Outputs
    • Plots on Datasets
      • MDS plot
      • Density Plot
      • Box Plot
    • Knowledge Base Coverage
      • Gene Coverage Plots
      • Pathway Coverage Plots
    • Feature Rankings
      • Ranking Overlaps
    • Feature Annotations and Enrichments
      • Annotation Overlaps
      • Enrichment Overlaps
    • Classification Performance
    • Feature Selection Runtimes
• Input Data Sets
  • Gene Expression Data
  • Metadata
  • Data for Cross-Validation
• Configuration Parameters
  • General
  • R
  • Java
  • Dataset
  • Preprocessing
  • Gene Selection - General
  • Gene Selection - Methods
  • Evaluation
  • Rankings
  • Classification
  • Prediction (not implemented yet)
  • Enrichr
  • OpenTargets
  • KEGG
  • UMLS (needed to transform search terms into CUIs for using DisGeNET)
  • DisGeNET
  • PathwayCommons
  • BiomaRt
  • gConvert
• Folder Structure - Where to find what Files (In- and Output)
  • input/
  • intermediate/
  • results/
• Knowledge Bases
  • DisGeNET
  • OpenTargets
  • KEGG
    • Retrieving Relevant Genes from Pathway Information
    • Gene Association Score Computation from Network Information
  • PathwayCommons
• Prior Knowledge Approaches
  • Modifying Prior Knowledge Approaches
    • Filtering
    • Extension
  • Combining Approaches
    • LassoPenalty
    • WeightedScore
  • Network/Pathway Approaches
    • NetworkActivity
    • CorgsNetworkActivity
• Extending Comprior - How-Tos
  • Add New Preprocessing Functionality
    • 1. Implement a new Preprocessor
    • 2. Update the Config File (optional)
    • 3. Include the Preprocessor in the Execution Pipeline
  • Add a New Knowledge Base
    • 1 Implement KnowledgeBase Class
    • 2 Implement a Pathway Parser (optional)
    • 3 Implement Web Service Accessing Class
    • 4 Update the Config File
    • 5 Register the Knowledge Base at KnowledgeBaseFactory
  • Add a new Feature Selector Approach
    • 1a. Implement a Feature Selector
    • 1b. Implement a Network Selector
    • 2. Update the Config File
    • 3. Register Feature/Network Selection Approach to the FeatureSelectorFactory
  • Add Custom Code from R/Java/another Programming Languages
    • Invoking R or Java Code
    • Invoking Code from Another Programming Language than R or Java
• Python Code Documentation
  • pipeline module
  • benchutils module
  • preprocessing module
  • featureselection module
  • knowledgebases module
  • evaluation module
• R Code Documentation
  • Feature Selection
  • Utility
• Java Code Documentation
  • Feature Selection
  • Evaluation
• System Architecture
  • Components Architecture
  • preprocessing Class Diagram
  • featureselection Class Diagram
  • knowledgebases Class Diagram
  • evaluation Class Diagram

Indices and tables

• Index
• Module Index
• Search Page