calculateRWHN: Calculate RWHN

In JoWatson2011/phosphoRWHN: Random Walk on Heterogeneous Network For Functional Analysis of Phosphoproteomics Data

Description

Calculate RWHN

Usage

calculateRWHN(
  hetNet,
  seeds,
  transitionProb,
  restart,
  eta_xy,
  eta_yz,
  eps = 1/10^6,
  random = F,
  filterFunctions = T
)

calculateTransitionMatrix(transitionProb, hetNet, vertices)

getRWHN(transMat, restart, eta_xy, eta_yz, seeds, eps)

heatmap_RWHN(
  rwhn_output,
  database = "",
  colours = c(low = "#e6e4f8", high = "#46009e"),
  removeCommon = T,
  pct_cutoff = 0.05
)

Arguments

hetNet	List; output of constructHetNet()
seeds	Character vector of seed nodes
transitionProb	Integer; transition probability
restart	Integer; restart probability
eta_xy	Integer; weighting on protein layer
eta_yz	Integer; weighting on function layer
eps	Integer; steady state defined by distance between p0 and p1
random	Logical; randomly permute edges? For control cases
filterFunctions	Remove functional annotations that are always ranked in the same position For visualisation:
vertices	Data frame; vertices in heterogeneous network, as contained in output of constructHetNet()
transMat	List; output of calculateTransitionMatrix()
rwhn_output	output of calculateRWHN() (or getRWHN())
database	character; name of annotation database
colours	character vector of length 2 with colours for scale
removeCommon	logical; if rwhn_output is a list, remove functions ranked at the same position in all cases. This is useful for removing noise.
pct_cutoff	numeric, default 0.05; top terms to be included in results output, as percentage.

Value

A data frame of ranked nodes from the functional layer

JoWatson2011/phosphoRWHN documentation built on Jan. 28, 2022, 4:02 a.m.