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DynCommPhylo

Phylogenetic Reconstruction via Dynamic Community Detection

This package includes functions for converting and simplifying the output of the TILES dynamic community detection algorithm so that it can be plotted as a phylogeny. Network simplification is conducted using the fast greedy modularity optimization algorithm.

To install the package run the following in R:

install.packages("devtools")
devtools::install_github("masonyoungblood/DynCommPhylo")

In order to use the functions included in this package, you need to have already analyzed your data with the Python implementation of TILES. The functions are currently only compatible with yearly TILES snapshots (e.g. 1970, 1971, 1972), but support for other timeframes will be added in future versions. The R workspace needs to include both the input file and a subdirectory called "output" that has the unzipped graph and strong-communities output files. A basic example of the core functions is below:

original_network <- network_construction(file = "edges.tsv", first_year = 1970, plot_years = c(1970:1999))
simplified_network <- network_simplification(links = original_network$links, nodes = original_network$nodes)
plot <- phylo_plotting(links = simplified_network$links, nodes = simplified_network$nodes)

The plotted phylogeny (D3.js sankey plot) can be saved as an interactive HTML file using htmlwidgets or as a static PNG file using r2d3.

htmlwidgets::saveWidget(plot, file = "phylogeny.html", title = "Phylogeny")
r2d3::save_d3_png(plot, file = "phylogeny.png", background = "white", width = 1000, height = 600, delay = 1, zoom = 10)

For more details about the methods in this package, check out the corresponding manuscript:

Youngblood, M., Baraghith, K., & Savage, P. E. (2020). Phylogenetic reconstruction of the cultural evolution of electronic music via dynamic community detection (1975–1999). arXiv: 2011.02460

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