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Diet Networks: Thin Parameters for Fat Genomics

Unofficial implementation of diet networks in TensorFlow.

tb

Requirements:

Usage:

  • Install the requirements above. Use plink2numpy to preprocess PLINK files and run dietnet script with --prefix option.
  • To reproduce 1000G results, install dietnet e.g. python setup.py install and run make command in 1000G folder. (~700MB file will be downloaded) Finally, run ./dietnet train 1000G/genotypes

TODO:

  • Dropout
  • Bias terms for We and Wd
  • Summary ops and tensorboard screenshots. also misclass. err
  • K-fold CV
  • Make train and predict subcommands e.g. add placeholders
  • Other embeddings: random projection, histogram
  • SNP2vec

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Diet networks in TensorFlow

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  • Python 95.4%
  • Makefile 4.6%