Return a data frame with features from the 2 largest nodes, 2 largest edges, 10 largest non-null paths, and all 8-week nodes from the graphical representation of training-regulated features in each tissue. This code replicates the graphical clusters for which pathway enrichment was performed for the landscape manuscript.
Value
a data frame with 5 columns and one row per combination of feature ID and cluster:
featurecharacter, unique feature identifier in the format 'MotrpacRatTraining6moData::ASSAY_ABBREV;MotrpacRatTraining6moData::TISSUE_ABBREV;feature_ID' only for training-regulated features at 5% IHW FDR. For redundant differential features, 'feature_ID' is prepended with the specific platform to make unique identifiers. See MotrpacRatTraining6moData::REPEATED_FEATURES for details.
clustercharacter, cluster label
omecharacter, assay abbreviation, one of MotrpacRatTraining6moData::ASSAY_ABBREV
tissuecharacter, tissue abbreviation, one of MotrpacRatTraining6moData::TISSUE_ABBREV
feature_IDcharacter, MoTrPAC feature identifier
Details
Notes about cluster labels:
All clusters are prefixed with the tissue abbreviation and a colon, e.g. "SKM-GN:"
Nodes are defined by the time point and state in each sex, where state is 1 for up, 0 for null, and -1 for down. For example, "1w_F-1_M-1" is a node that characterizes molecules at the "1w" time point that are down-regulated in females ("F-1") and down-regulated in males ("M-1"). These three pieces of information (time point, female state, male state) are separated by underscores ("_")
Edges contain "---" and connect a pair of nodes
Paths contain "->" and connect four nodes