target_edge_list

Combined graph (iGraph graph object) for a specific group

graph

Data frame. Has column `node_id` (unique node IDs in the iGraph graph
object that are targeted by drugs) and columns `group1` and `group2` (boolean values specifying
 whether the node is contained in the combined graph of the group)

target_nodes

Character. Indicates which group is analyzed.

group

(INTERNAL) Based on the supplied graph and target nodes this function returns a
list of edges that are directly adjacent to target nodes. These edges can be used for further
computation to find differential scores in the networks.

Networks provide a means to incorporate molecular interactions into
reasoning, but on the omics-level, they are currently mainly used to combine
genomic and proteomic information. We here present a novel network analysis
pipeline that enables integrative analysis of multi-omics data including
metabolomics. It allows for comparative conclusions between two different
conditions, such as tumor subgroups, healthy vs. disease, or generally control
vs. perturbed.
Our approach focuses on interactions and their strength instead of on node
properties and includes molecules with low abundance and unknown function. We
use correlation-induced networks that are reduced and combined to form
heterogeneous, multi-omics molecular networks. Prior information such as
metabolite-protein interactions are incorporated. A semi-local, path-based
integration step denoises the network and ensures integrative conclusions. As
case studies, we investigate differential drug response in breast cancer tumor
datasets providing proteomics, transcriptomics, phospho-proteomics and
metabolomics data and contrasting patients with different estrogen receptor
status.
Our proposed pipeline leverages multi-omics data for differential predictions,
e.g. on drug response, and includes prior information on interactions.
The case study presented in the vignette uses data published by
Krug (2020) <doi:10.1016/j.cell.2020.10.036>. The package license applies only
to the software and explicitly not to the included data.

target_edge_list: Edges adjacent to target nodes

Description

Usage

Arguments

Value