Example use case on Kundaje lab cluster for SVM input generation:
/mnt/lab_data2/annashch/alzheimers_parkinsons/svm_pipeline/make_inputs
Execute scripts in make_inputs to generate input files for SVM model training.
Execute scripts in train_predict to train SVM models and get model predictions.
Execute scripts in score to get auPRC & other metrics of model performance.
Execute scripts in interpret to run gkmexplain interpretation.
Execute scripts in plot_interpretations to plot gkmexplain interpretations.
Execute util.gkmexplain_to_bigwig.py to generate a bigwig representation of gkmexplain scores
Note: SVM models for ENCODE tier 1 lines have been pre-trained and stored on oak at this location:
/oak/stanford/groups/akundaje/projects/chrombpnet/svm/dnase
/oak/stanford/groups/akundaje/projects/chrombpnet/svm/atac
Predictions for bQTL datasets ref & alt alleles are here:
/oak/stanford/groups/akundaje/projects/chrombpnet/svm/bQTL
Predictions genomewide for models trained on tier 1 DNASE data are here:
/oak/stanford/groups/akundaje/projects/chrombpnet/svm/genomewide_encode_tier1_lines_dnase