run_COSMOS_metabolism_to_signaling {cosmosR} | R Documentation |
Runs COSMOS from metabolism to signaling. This function uses CARNIVAL to find
a subset of the prior knowledge network based on optimization that (1)
includes the most measured and input nodes and (2) which is in agreement with
the data. Use preprocess_COSMOS_metabolism_to_signaling
to
prepare the the inputs, measurements and the prior knowledge network.
run_COSMOS_metabolism_to_signaling( data, CARNIVAL_options = default_CARNIVAL_options() )
data |
|
CARNIVAL_options |
List that controls the options of CARNIVAL. See details
in |
List with the following elements:
weightedSIF
The averaged networks found by optimization in a format of a Simple Interaction network, i.e. each row codes an edge
N_networks
Number of solutions found by the optimization
nodesAttributes
Estimated node properties
individual_networks
List of optimial networks found
individual_networks_node_attributes
Node activity in each network
preprocess_COSMOS_metabolism_to_signaling
,
runCARNIVAL
, cosmos_data
CARNIVAL_options <- cosmosR::default_CARNIVAL_options() CARNIVAL_options$solver <- "lpSolve" data(toy_network) data(toy_signaling_input) data(toy_metabolic_input) data(toy_RNA) test_back <- preprocess_COSMOS_metabolism_to_signaling(meta_network = toy_network, signaling_data = toy_signaling_input, metabolic_data = toy_metabolic_input, diff_expression_data = toy_RNA, maximum_network_depth = 15, remove_unexpressed_nodes = TRUE, CARNIVAL_options = CARNIVAL_options ) test_result_back <- run_COSMOS_metabolism_to_signaling(data = test_back, CARNIVAL_options = CARNIVAL_options)