Drug Response Prediction from Differential Multi-Omics Networks

---

Documentation for package ‘DrDimont’ version 0.1.4

• DESCRIPTION file.
• User guides, package vignettes and other documentation.

Help Pages

check_input	Check pipeline input data for required format
combined_graphs_example	Combined graphs
compute_correlation_matrices	Computes correlation matrices for specified network layers
compute_drug_response_scores	Calculate drug response score
correlation_matrices_example	Correlation matrices
determine_drug_targets	Determine drug target nodes in network
differential_graph_example	Differential graph
drdimont_settings	Create global settings variable for DrDimont pipeline
drug_gene_interactions	Drug-gene interactions
drug_response_scores_example	Drug response score
drug_target_edges_example	Drug target nodes in combined network
generate_combined_graphs	Combines individual layers to a single graph
generate_differential_score_graph	Compute difference of interaction score of two groups
generate_individual_graphs	Builds graphs from specified network layers
generate_interaction_score_graphs	Computes interaction score for combined graphs
individual_graphs_example	Individual graphs
install_python_dependencies	Installs python dependencies needed for interaction score computation
interaction_score_graphs_example	Interaction score graphs
layers_example	Formatted layers object
make_connection	Specify connection between two individual layers
make_drug_target	Reformat drug-target-interaction data
make_layer	Creates individual molecular layers from raw data and unique identifiers
metabolite_data	Metabolomics data
metabolite_protein_interactions	Metabolite protein interaction data
mrna_data	mRNA expression data
phosphosite_data	Phosphosite data
protein_data	Protein data
return_errors	Return detected errors in the input data
run_pipeline	Execute all DrDimont pipeline steps sequentially