An S3 class that combines the required data into a comprehensive list. Use
the preprocess_COSMOS_signaling_to_metabolism
or
preprocess_COSMOS_metabolism_to_signaling
to create an instance.
Usage
cosmos_data(
meta_network,
tf_regulon = NULL,
signaling_data,
metabolic_data,
expression_data,
verbose = TRUE
)
Arguments
- meta_network
Prior knowledge network (PKN). By default COSMOS use a PKN derived from Omnipath, STITCHdb and Recon3D. 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).
- expression_data
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. Genes with NA values are considered none expressed and they will be removed from the TF-gene expression interactions.
- verbose
(default: TRUE) Reports details about the
cosmos_data
object.