parsomics : a data-driven framework for metagenomics data integration powered by a local relational database

Abstract Motivation Metagenomics enables the analysis of complex microbial communities directly from environmental samples, resulting in massive datasets that are processed using multiple tools and workflows. Data integration is key for metagenomics research, however, challenges in data organization and management locally remain open in existing workflows. Results We present parsomics, a lightweight and extensible data management tool designed for efficient local storage, organization, and integration of metagenomic analysis results. Built upon PostgreSQL and implemented in Python, parsomics leverages a user-defined configuration file to automatically construct a relational database tailored to metagenomics-based data. It is user-friendly, easy to deploy, and implements modular plugin-based extensions to support diverse data types and outputs. parsomics can be installed in every major GNU/Linux environment and currently focuses on prokaryotic metagenomics analysis. Availability and implementation parsomics is an open-source project and its source code is available at https://gitlab.com/parsomics under the GPLv3 license. Comprehensive documentation can be found at https://parsomics.org and https://api.parsomics.org.