Exemplary intermediate pipeline output: Individual graphs example data built by
generate_individual_graphs
. Graphs were created from
correlation_matrices_example and
reduced by the `pickHardThreshold` reduction method. Used settings were:
individual_graphs_example
A named list with 2 items.
A named list with two groups.
Graph
Graph
Graph
Graph
A named list containing data frames of mappings of assigned node IDs to the user-provided component identifiers for nodes in `groupA` or `groupB` and all nodes
Data frame
Data frame
Data frame
Data frame
settings <- drdimont_settings(
reduction_method=list(default="pickHardThreshold"),
r_squared=list(
default=0.8,
groupA=list(metabolite=0.45),
groupB=list(metabolite=0.15)),
cut_vector=list(
default=seq(0.3, 0.7, 0.01),
metabolite=seq(0.1, 0.65, 0.01)))
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 and individual graphs. They were created from data stratified by estrogen
receptor (ER) status: `groupA` contains data of ER+ patients and `groupB` of
ER- patients.