# Predicting Differential Drug Response using Multi-Omics Networks

## Documentation for package ‘molnet’ version 0.1.0

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

## Help Pages

calculate_interaction_score | Calls a python script to calculate interaction score for combined graphs
check_connection | Checks connection
check_drug_target | Check drug target interaction data
check_drug_targets_in_layers | Check drug target and layer data
check_input | Check pipeline input data for required format
check_layer | Check layer input
check_sensible_connections | Check connection and layer data
chunk | Create chunks from a vector for parallel computing
chunk_2gether | Create chunks from two vectors for parallel computing
combined_graphs_example | Combined graphs
combine_graphs | Combining graphs by adding inter-layer edges
corPvalueStudentParallel | Compute p-values for upper triangle of correlation matrix in parallel
create_unique_layer_node_ids | Assigns node IDs to the biological identifiers across a graph layer
determine_drug_targets | Determine drug target nodes in network
differential_score | The absolute difference of interaction score of two groups
differential_score_graph_example | Differential graph
drug_gene_interactions | Drug-gene interactions
drug_response_score_example | Drug response score
drug_targets_example | Drug target nodes in combined network
drug_target_interaction_example | Drug target interaction example data
find_targets | Filter drug target nodes
generate_combined_graphs | Combines individual layers to a single graph
generate_individual_graphs | Builds graphs from specified network layers
generate_reduced_graph | Generate a reduced iGraph
get_drug_response_score | Calculate drug response score
get_layer | [INTERNAL] Fetch layer by name from layer object
get_layer_setting | Get layer settings
graph_metrics | Analyses metrics of an iGraph object
individual_graphs_example | Individual graphs
install_python_dependencies | Installs python dependencies needed for interaction score computation
interaction_score | Computes interaction score for combined graphs
interaction_score_graphs_example | Interaction score graphs
interaction_score_graphs_vignette | Interaction score graphs for vignette
inter_layer_edgelist_by_id | Interlayer conntections by identifiers
inter_layer_edgelist_by_table | Interaction table to iGraph graph object
layers_example | Formatted layers object
load_interaction_score_output | Loads output of python script for interaction score calculation
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_interaction | Metabolite protein interaction data
molnet_settings | Create global settings variable for molnet pipeline
mrna_data | mRNA expression data
network_reduction_by_pickHardThreshold | Reduces network based on WGCNA::pickHardThreshold function
network_reduction_by_p_value | Reduce the the entries in an adjacency matrix by thresholding on p-values
phosphoprotein_data | Phosphosite data
pickHardThreshold_alternative | Alternative implementation of WGCNA::pickHardThreshold
protein_data | Protein data
return_errors | Return detected errors
sample_size | Sample size for correlation computation
scaleFreeFitIndex_alternative | Alternative implementation of WGCNA::scaleFreeFitIndex
set_cluster | Create and register cluster
shutdown_cluster | Shutdown cluster and remove corresponding connections
start_pipeline | Execute all molnet-pipeline steps sequentially
target_edge_list | Edges adjacent to target nodes
write_interaction_score_input | Write edge lists and combined graphs to files