preprocess_COSMOS_signaling_to_metabolism {cosmosR} | R Documentation

## Preprocess COSMOS Inputs For Signaling to Metabolism

### Description

Runs checks on the input data and simplifies the prior knowledge network. Simplification includes the removal of (1) nodes that are not reachable from signaling nodes and (2) interactions between transcription factors and target genes if the target gene does not respond or the response is contradictory with the change in the transcription factor activity. Optionally, further TF activities are estimated via network optimization via CARNIVAL and the interactions between TF and genes are filtered again.

### Usage

    preprocess_COSMOS_signaling_to_metabolism(
      meta_network = meta_network,
      tf_regulon = load_tf_regulon_dorothea(),
      signaling_data,
      metabolic_data,
      diff_expression_data,
      diff_exp_threshold = 1,
      maximum_network_depth = 8,
      expressed_genes = names(diff_expression_data)[!is.na(diff_expression_data)],
      remove_unexpressed_nodes = TRUE,
      filter_tf_gene_interaction_by_optimization = TRUE,
      CARNIVAL_options = default_CARNIVAL_options()
    )

### Arguments

`meta_network` | prior knowledge network (PKN). A PKN released with COSMOS and derived from Omnipath, STITCHdb and Recon3D can be used. See details on the data `meta_network`.
`tf_regulon` | collection of transcription factor - target interactions. A default collection from dorothea can be obtained by the `load_tf_regulon_dorothea` function.
`signaling_data` | numerical vector, where names are signaling nodes in the PKN and values are from {1, 0, -1}. Continuous data will be discretized using the `sign` function.
`metabolic_data` | numerical vector, where names are metabolic nodes in the PKN and values are continuous values that represents log2 fold change or t-values from a differential analysis. These values are compared to the simulation results (simulated nodes can take value -1, 0 or 1)
`diff_expression_data` | (optional) numerical vector that represents the results of a differential gene expression analysis. Names are gene names using EntrezID starting with an X and values are log fold change or t-values. `convert_genesymbols_to_entrezid` can be used for conversion. We use the “`diff_exp_threshold`” parameter to decide which genes changed significantly. Genes with NA values are considered none expressed and they will be removed from the TF-gene expression interactions.
`diff_exp_threshold` | threshold parameter (default 1) used to binarize the values of “`diff_expression_data`”.
`maximum_network_depth` | integer > 0 (default: 8). Nodes that are further than “`maximum_network_depth`” steps from the signaling nodes on the directed graph of the PKN are considered non-reachable and are removed.
`expressed_genes` | character vector. Names of nodes that are expressed. By default we consider all the nodes that appear in `diff_expression_data` with a numeric value (i.e. nodes with NA are removed)
`remove_unexpressed_nodes` | if TRUE (default) removes nodes from the PKN that are not expressed, see input “`expressed_genes`”.
`filter_tf_gene_interaction_by_optimization` | (default:TRUE), if TRUE then runs a network optimization that estimates TF activity not included in the inputs and checks the consistency between the estimated activity and change in gene expression. Removes interactions where TF and gene expression are inconsistent
`CARNIVAL_options` | list that controls the options of CARNIVAL. See details in `default_CARNIVAL_options`.

### Value

cosmos_data object with the following fields:

`meta_network`

  Filtered PKN

`tf_regulon`

  TF - target regulatory network

`signaling_data_bin`

  Binarised signaling data

`metabolic_data`

  Metabolomics data

`diff_expression_data_bin`

  Binarized gene expression data

`optimized_network`

  Initial optimized network if `filter_tf_gene_interaction_by_optimization is TRUE`

### See Also

`meta_network` for meta PKN, `load_tf_regulon_dorothea` for tf regulon, `convert_genesymbols_to_entrezid` for gene conversion, `runCARNIVAL`.

### 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_for <- preprocess_COSMOS_signaling_to_metabolism(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
    )

[Package cosmosR version 1.2.0 Index]