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SOM_Seq_Sim 1.0 documentation
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SOM_Seq_Sim 1.0 documentation

Project Overview

  • SOM-Seq
  • Data Overview
  • Core Function Descriptions
    • SOM Core Functions
    • Seq_Sim Core Functions

Setup & Walkthroughs

  • Installation Instructions
  • Generating Sequencing Data
  • Creating SOMs
  • Inputs
  • Usage
  • Outputs
  • Walkthroughs
    • Seq Sim Workflow
      • 1. Imports
      • 2. Specify Number of Samples and Fold Change
      • 3. Specify Configuration File Parameters
      • 4. Generate and Save Sequencing Data
      • 5. Ensure files were saved properly
    • SOM Example Iris
      • Basic Example of Using the Self-Organizing Map (SOM) Class
      • 1. Imports
      • 2. Load Data
      • 3. Train SOM
      • 4. Get Fit Metrics
      • 5. Plot SOM’s (see output directory for figures)
    • SOM Example Seq
      • Application of Self-Organizing Maps (SOM) for Cell Type Identification
      • 1. Imports
      • 2. Load Data
      • 3. Train SOM
      • 4. Plot layout of SOM with neuron IDs
      • 5. Plot component planes and categorical data (see output directory for figures)
      • 6. Custom plotting for seq visualization for each neuron
    • SOM Example Titanic
      • Hyperparameter Tuning Example for Self-Organizing Maps (SOM)
      • 1. Imports
      • 2. Load Data
      • 3. Define Hyperparameters
      • 4. Grid Search for Optimal Parameters
      • 5. Show the best parameters
      • 6. Train SOM
      • 7. Get the Fit Metrics
      • 8. Plot component planes and categorical data (see output directory for figures)

Resources

  • References & Acknowledgements
  • Link to Github
  • Contributing to SOM_Seq_Sim
  • Code of Conduct - SOM_Seq_Sim
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Python Module Index

s
 
s
- Seq_Sim
    Seq_Sim.utils.seq_sim_utils
- SOM
    SOM.utils.som_utils
Copyright © 2024, Victoria Hurd
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