| combined_graphs_example {DrDimont} | R Documentation |
Combined graphs
Description
Exemplary intermediate pipeline output: Combined graphs example data built by
generate_combined_graphs. Combined graphs were built
using the individual_graphs_example and:
Usage
combined_graphs_example
Format
A named list with 2 items.
- graphs
A named list with two groups.
- groupA
Graph associated with 'groupA'
- groupB
Graph associated with 'groupB'
- annotations
A data frame of mappings of assigned node IDs to the user-provided component identifiers for all nodes in 'groupA' and 'groupB' together and all layers
- both
Data frame
Details
inter_layer_connections = list(
make_connection(from='mrna', to='protein', connect_on='gene_name', weight=1),
make_connection(from='protein', to='phosphosite', connect_on='gene_name', weight=1),
make_connection(from='protein', to='metabolite', connect_on=metabolite_protein_interactions, weight='combined_score'))
A subset of the original data by Krug et al. (2020) and randomly sampled metabolite
data from layers_example was used to generate the correlation
matrices, individual graphs and combined graphs. They were created from data
stratified by estrogen receptor (ER) status: 'groupA' contains data of ER+
patients and 'groupB' of ER- patients.
Source
Krug, Karsten et al. “Proteogenomic Landscape of Breast Cancer Tumorigenesis and Targeted Therapy.” Cell vol. 183,5 (2020): 1436-1456.e31. doi:10.1016/j.cell.2020.10.036