Discussion
The field of phylogenomics relies on a broad range of efficient software for many operations in a typical workflow (e.g., raw read assembly, tree inference), but other aspects of standard analysis pipelines are neglected. We developed SEGUL to fill a need for software that can manipulate alignment files and calculate summary statistics in a manner suitable for computational experts and novices alike. SEGUL offers consistently fast operations, low memory demands, and efficient CPU use across all supported features. The convenient features of SEGUL (e.g., GUI support, safe command line application) offer an easy introduction for beginners with no cost to performance for advanced users.
There is an increasing trend of relaying to containerized applications (i.e., using Docker and Singularity) to solve dependency issues, but this fix makes it harder for computing novices to study phylogenomics. We take a different approach by minimizing dependencies to simplify installation. We add GUI support to further aid evolutionary biologists who prefer the convenience of a GUI, while retaining efficiency and reproducibility. Using GUI version may also be more convenient to perform the tasks on small datasets (e.g., Sanger sequencing datasets), and for introductory teaching situations.
SEGUL support for mobile devices enables a new way to perform phylogenomic data manipulation and summary statistics. Our application facilitates teaching phylogenomics to students who use mobile devices (e.g., tablets) as their primary computers. Many authors publish their alignments (e.g., Jarvis et al., 2014; Oliveros et al., 2019, https://github.com/roblanf/BenchmarkAlignments) and phylogenetic tree estimation can be conducted on the web (DeSalle et al., 2020). Our application allows the entire process from alignment inspection and concatenation to phylogenetic tree estimation to be conducted from a mobile device. Mobile devices are becoming more powerful, with some tablets, such as Apple’s iPad Pro and iPad Air, using the same processors as their laptop and desktop counterparts. Future implementations to exploit mobile device strengths, such as touch input, would enhance the benefits of mobile applications for phylogenomic data manipulations.
We achieve a cross-platform, high-performance application by writing our GUI code in Flutter and handling expensive computation in Rust. Our implementation of this approach in the neglected aspects of typical phylogenomic workflows provides proof of concept in the development and scaling of high-performance applications with GUI interaction on desktop and mobile operating systems. Extension of our approach to other aspects of phylogenomic workflows would pave the way for more user-friendly software to study phylogenomics and enable teaching students with limited access to computational power.