makeFeatureModelPrevalenceNetworkCooccur: Prints as text the detail on a given experiment along with...

In predomics/predomicspkg: Interpretable Prediction in Omics Data

Prints as text the detail on a given experiment along with summarized results (if computed)

Description

This function will use the coocur package to compute the co-occurance of features in a population of models

Usage

makeFeatureModelPrevalenceNetworkCooccur(
  pop.noz,
  feature.annot,
  alpha = 0.05,
  verbose = TRUE,
  layout = "circlular"
)

Arguments

pop.noz:	a data.frame of in features in the rows and models in the columns. This table contains the feature coefficients in the models and is obtained by makeFeatureAnnot()
feature.annot:	a data frame with annotation on features obtained by makeFeatureAnnot()
alpha:	the significane p-value of the co-occurance.
verbose:	print out information during run
layout:	the network layout by default is circular (layout_in_circle) and will be a weighted Fruchterman-Reingold otherwise

Value

plots a graph

predomics/predomicspkg documentation built on Dec. 11, 2024, 11:06 a.m.