thepanlab/GattacaNet

predictive genomics

GattacaNet

Predictive Genomics for breast cancer

Requirements

• Python 3.6
  • Tensoflow v1.13
  • pandas_plink
  • pandas
  • numpy
  • sklearn v0.22
  • DeepExplain
    • https://github.com/marcoancona/DeepExplain/
  • LIME
    • https://github.com/marcotcr/lime
• R
  • bwgr
  • read.plink
• LDpred
  • https://github.com/bvilhjal/ldpred

How to use it

This github contains the base code to run our experimentations. Each module represent a step of analysis.

• DataPartioning
  • Comports the data partioning notebooks
• DataProcessingScript
  • Comports the data Processing scripts to extract SNPs significiant
• Learning
  • Full_vs_Reduced
    • Comport the notebooks to analyze the optimal SNP reduction
  • Architecture Comparison
    • Comport the notebooks to compare architectures
  • Classic_Machine_Learning
    • Comport the notebook to compare the classic machine learning models
  • Classic_Bio_Learning_Technics
    • Comport the R scripts to analyze BLUP, BayesA.... and the bash script for LDpred
• Interpretation
  • Comport the notbooks for LIME and DeepLift