Heatmaps for Multiple Network Data

Simplify the exploratory data analysis process for multiple network data sets with the help of hierarchical clustering and heatmaps. Multiple network data consists of multiple disjoint networks that share common graph, node and edge variables. Contains the tools necessary to convert this raw data into a single dynamic report, summarizing the relationships of the graph, node and structural characteristics of the networks.


neatmaps

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The goal of the neatmaps package is to simplify the exploratory data analysis process for multiple network data sets with the help of hierarchical clustering and heatmaps. Multiple network data consists of multiple disjoint networks that share common graph, node and edge variables. This package contains the necessary tools to convert this raw data into a dynamic report, summarizing the relationships between the graph, node and structural characteristics of the networks.

Installation

# To install neatmaps, simply run the following code:
install.packages('neatmaps')

Code Example

library(neatmaps)
 
# Create a "cleaned" dataframe using the netsDataFrame function
df <- netsDataFrame(net.attr.df = networkAttrDF,
                    node.attr.df = nodeAttrDF,
                    edge.df = edgeDF)
 
# Run the neatmap function on the dataframe. This will produce a list
# consisting of the dendrogram of the networks' variables, the significant
# clusters of the bootstrap analysis, the results of the statistical analysis
# and the heatmap.
resultsList <- neatmap(df, scale.df = "basic", mainTitle = "Heatmap", 
                   xlabel = "", ylabel = "Networks",
                   link.method = "single", dist.method = "euclidean",
                   nBootRep = 100, xlabCex = 1, ylabCex = 1,
                   heatmapMargins = c(100, 50, 50, 100))

To display the heatmap:

resultsList[[4]]

Dynamic Report

A dynamic report template has been included in the inst/rmd directory. Follow the instruction at the top of template.Rmd to create a dynamic report using your own data.

Documentation

Available on CRAN.

News

Reference manual

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install.packages("neatmaps")

1.0.7 by Phil Boileau, 2 months ago


https://github.com/PhilBoileau/neatmaps


Browse source code at https://github.com/cran/neatmaps


Authors: Phil Boileau [aut, cre]


Documentation:   PDF Manual  


MIT + file LICENSE license


Imports igraph, heatmaply, pvclust, ggplot2, dendextend


See at CRAN