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SEGUL: Ultrafast, memory-efficient and mobile-friendly software for manipulating and summarizing phylogenomic datasets.
Handika, Heru; Esselstyn, Jacob A.
Affiliation
  • Handika H; Museum of Natural Science and Department of Biological Sciences, Louisiana State University, Baton Rouge, Louisiana, USA.
  • Esselstyn JA; Museum of Natural Science and Department of Biological Sciences, Louisiana State University, Baton Rouge, Louisiana, USA.
Mol Ecol Resour ; : e13964, 2024 Apr 26.
Article in En | MEDLINE | ID: mdl-38666432
ABSTRACT
Phylogenetic studies now routinely require manipulating and summarizing thousands of data files. For most of these tasks, currently available software requires considerable computing resources and substantial knowledge of command-line applications. We develop an ultrafast and memory-efficient software, SEGUL, that performs common phylogenomic dataset manipulations and calculates statistics summarizing essential data features. Our software is available as standalone command-line interface (CLI) and graphical user interface (GUI) applications, and as a library for Rust, R and Python, with possible support of other languages. The CLI and library versions run native on Windows, Linux and macOS, including Apple ARM Macs. The GUI version extends support to include mobile iOS, iPadOS and Android operating systems. SEGUL leverages the high performance of the Rust programming language to offer fast execution times and low memory footprints regardless of dataset size and platform choice. The inclusion of a GUI minimizes bioinformatics barriers to phylogenomics while SEGUL's efficiency reduces economic barriers by allowing analysis on inexpensive hardware. Our support for mobile operating systems further enables teaching phylogenomics where access to computing power is limited.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Mol Ecol Resour Year: 2024 Type: Article Affiliation country: United States

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Mol Ecol Resour Year: 2024 Type: Article Affiliation country: United States