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speakeasyR  

Fast and Robust Multi-Scale Graph Clustering
View on CRAN: Click here


Download and install speakeasyR package within the R console
Install from CRAN:
install.packages("speakeasyR")

Install from Github:
library("remotes")
install_github("cran/speakeasyR")

Install by package version:
library("remotes")
install_version("speakeasyR", "0.1.4")



Attach the package and use:
library("speakeasyR")
Maintained by
David Connell
[Scholar Profile | Author Map]
First Published: 2024-06-18
Latest Update: 2024-08-19
Description:
A graph community detection algorithm that aims to be performant on large graphs and robust, returning consistent results across runs. SpeakEasy 2 (SE2), the underlying algorithm, is described in Chris Gaiteri, David R. Connell & Faraz A. Sultan et al. (2023) <doi:10.1186/s13059-023-03062-0>. The core algorithm is written in 'C', providing speed and keeping the memory requirements low. This implementation can take advantage of multiple computing cores without increasing memory usage. SE2 can detect community structure across scales, making it a good choice for biological data, which often has hierarchical structure. Graphs can be passed to the algorithm as adjacency matrices using base 'R' matrices, the 'Matrix' library, 'igraph' graphs, or any data that can be coerced into a matrix.
How to cite:
David Connell (2024). speakeasyR: Fast and Robust Multi-Scale Graph Clustering. R package version 0.1.4, https://cran.r-project.org/web/packages/speakeasyR. Accessed 29 Mar. 2025.
Previous versions and publish date:
0.1.0 (2024-06-18 16:40), 0.1.2 (2024-07-29 19:00), 0.1.3 (2024-08-20 11:40)
Other packages that cited speakeasyR R package
View speakeasyR citation profile
Other R packages that speakeasyR depends, imports, suggests or enhances
Complete documentation for speakeasyR
Functions, R codes and Examples using the speakeasyR R package
Full speakeasyR package functions and examples
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