edgesToHubNetworks: Convert a Two-column Matrix or Data Frame into a Hub Node...

In ClassifyR: A framework for cross-validated classification problems, with applications to differential variability and differential distribution testing

Description

Interactions between pairs of features (typically a protein-protein interaction, commonly abbreviated as PPI, database) are restructured into a named list. The name of the each element of the list is a feature and the element contains all features which have an interaction with it.

Usage

  edgesToHubNetworks(edges, minCardinality = 5)

Arguments

edges	A two-column matrix or data.frame for which each row specifies a known interaction betwen two interactors. If feature X appears in the first column and feature Y appears in the second, there is no need for feature Y to appear in the first column and feature X in the second.
minCardinality	An integer specifying the minimum number of features to be associated with a hub feature for it to be present in the result.

Value

An object of type FeatureSetCollection.

Author(s)

Dario Strbenac

References

VAN: an R package for identifying biologically perturbed networks via differential variability analysis, Vivek Jayaswal, Sarah-Jane Schramm, Graham J Mann, Marc R Wilkins and Yee Hwa Yang, 2010, BMC Research Notes, Volume 6 Article 430, https://bmcresnotes.biomedcentral.com/articles/10.1186/1756-0500-6-430.

Examples

  interactor <- c("MITF", "MITF", "MITF", "MITF", "MITF", "MITF",
                  "KRAS", "KRAS", "KRAS", "KRAS", "KRAS", "KRAS",
                  "PD-1")
  otherInteractor <- c("HINT1", "LEF1", "PSMD14", "PIAS3", "UBE2I", "PATZ1",
                       "ARAF", "CALM1", "CALM2", "CALM3", "RAF1", "HNRNPC",
                       "PD-L1")
  edges <- data.frame(interactor, otherInteractor, stringsAsFactors = FALSE)
  
  edgesToHubNetworks(edges, minCardinality = 4)

ClassifyR documentation built on Nov. 8, 2020, 6:53 p.m.