GARS_PlotFeaturesUsage: A bubble chart to assess the usage of each features

In GARS: GARS: Genetic Algorithm for the identification of Robust Subsets of variables in high-dimensional and challenging datasets

Description

This function allows assessing visually how many times a feature is selected across the generations. In principle, a highly recurring feature is more likely to be important.

Usage

GARS_PlotFeaturesUsage(popul.list, allFeat, nFeat = length(allFeat))

Arguments

popul.list	A SummarizedExpression object
allFeat	A character vector containing the list of the all features name. Often, it corresponds to the columns name of the data matrix.
nFeat	The number of features which have to be plotted. Default is 'length(allFeat)'

Value

A bubble chart where each plotted feature is represented by a colored circle. A feature is important (i.e. conserved) if the size is wide and the color tends to red; the smaller the size, the lighter the color and less informative the feature.

Author(s)

Mattia Chiesa, Luca Piacentini

See Also

GARS_PlotFitnessEvolution

Examples

# use example data:
data(GARS_data_norm)
data(GARS_pop_list)
allfeat_names <- colnames(GARS_data_norm)
GARS_PlotFeaturesUsage(GARS_pop_list, allfeat_names, nFeat = 10)

GARS documentation built on Nov. 8, 2020, 7:23 p.m.