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Deep learning in predicting functional effects of noncoding variants in brain-specific disorders

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deepPsych

Deep learning in predicting functional effects of noncoding variants in brain-specific disorders

Steps:

  1. Data preprocessing (e.g. RNA-seq, CHIP-seq, ATAC-seq, etc.)
  2. Data and Label extraction for genomic bins (of interest)
  3. Numpy conversion of data and labels (for DL usage)
  4. DL training/Validation/Testing (demonstrated in Training 3 subdirectory)

Note: A complete pipeline (R-based) automating the steps 1-3 can be found in full_pipeline.R.

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Deep learning in predicting functional effects of noncoding variants in brain-specific disorders

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