Predicting Differential Drug Response using Multi-Omics Networks

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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