# ParallelEvolCCM: Quantifying Coevolutionary Patterns Among Genomic Features

## TL;DR

This paper introduces ParallelEvolCCM, a tool that improves the analysis of coevolutionary patterns among genomic features by adding parallelization and filtering options.

## Contribution

The novel contribution is the R wrapper for the Community Coevolution Model with parallelization and pre-filtering capabilities.

## Key findings

- ParallelEvolCCM increases the efficiency of coevolutionary comparisons through parallelization.
- The tool was applied to a dataset of 1000 Bifidobacterium genomes to demonstrate its functionality.
- The implementation is open-source and available for use under the MIT license.

## Abstract

Concerted gains and losses of genomic features such as genes and mobile genetic elements can provide key clues into related functional roles and shared evolutionary trajectories. By capturing phylogenetic signals, a coevolutionary model can outperform comparative methods based on shared presence and absence of features. We previously developed the Community Coevolution Model, which represents the gain/loss probability of each feature as a combination of its own intrinsic rate, combined with the joint probabilities of gain and loss with all other features. Originally implemented as an R library, we have now developed an R wrapper that adds parallelization and several options to pre-filter the features to increase the efficiency of comparisons. Here we describe the functionality of ParallelEvolCCM and apply it to a dataset of 1000 genomes of the genus Bifidobacterium. ParallelEvolCCM is released under the MIT license and available at https://github.com/beiko-lab/arete/blob/master/bin/ParallelEvolCCM.R.