run_COSMOS_metabolism_to_signaling {cosmosR} | R Documentation

## run COSMOS metabolism to signaling

### Description

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.

### Usage

    run_COSMOS_metabolism_to_signaling(
      data,
      CARNIVAL_options = default_CARNIVAL_options()
    )

### Arguments

`data` | `cosmos_data` object. Use the `preprocess_COSMOS_metabolism_to_signaling` function to create an instance.
`CARNIVAL_options` | List that controls the options of CARNIVAL. See details in `default_CARNIVAL_options`.

### Value

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

### See Also

`preprocess_COSMOS_metabolism_to_signaling`, `runCARNIVAL`, `cosmos_data`

### Examples

    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)

[Package cosmosR version 1.2.0 Index]