Academic Journal

AgrOmicSo: A client-server interface for accessible large-scale analysis of next-generation sequencing data.

Bibliographic Details
Title: AgrOmicSo: A client-server interface for accessible large-scale analysis of next-generation sequencing data.
Authors: Lee DJ; Supercomputing Center, National Institute of Agricultural Science, Jeonju, Republic of Korea., Lee TH; Supercomputing Center, National Institute of Agricultural Science, Jeonju, Republic of Korea., Kwon T; Corporate R&D Center, Cloud9, Cheongju-si, Republic of Korea.
Source: PloS one [PLoS One] 2026 Jun 01; Vol. 21 (6), pp. e0348571. Date of Electronic Publication: 2026 Jun 01 (Print Publication: 2026).
Publication Type: Journal Article
Language: English
Journal Info: Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE
Imprint Name(s): Original Publication: San Francisco, CA : Public Library of Science
MeSH Terms: High-Throughput Nucleotide Sequencing*/methods , Computational Biology*/methods , Software* , User-Computer Interface*, Algorithms ; Humans
Abstract: The analysis of large-scale next-generation sequencing (NGS) data requires substantial computational power, often necessitating the use of high-performance computing (HPC) environments. However, the command-line interfaces for these resources create a significant barrier for many researchers. To bridge this gap, we developed AgrOmicSo (Agri-bio Omics Solution), a software solution designed as a user-friendly interface to a powerful server-side analysis engine. AgrOmicSo's client-server architecture allows researchers to manage and execute complex, large-scale NGS data analysis pipelines on a remote server directly from an intuitive graphical user interface on their local computer. The software integrates a comprehensive suite of bioinformatics tools for quality control, read mapping, variant calling, and annotation. Notably, it supports three distinct variant calling algorithms-GATK, DeepVariant, and VarScan-offering users flexibility for their specific research needs. AgrOmicSo provides both a "One-Step" mode for rapid, automated batch processing and a "Step-by-Step" mode for detailed, customized analyses. This paper describes the architecture, implementation, and utility of AgrOmicSo as an interface for large-scale genomic analysis, highlighting its potential to advance research by making powerful computational resources more accessible, efficient, and reproducible for a broader scientific community. The client and server program of AgrOmicSo are freely available at https://agromicso.com.
(Copyright: © 2026 Lee et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)
Competing Interests: The authors have declared that no competing interests exist.
Entry Date(s): Date Created: 20260601 Date Completed: 20260717 Latest Revision: 20260726
Update Code: 20260726
PubMed Central ID: PMC13225662
DOI: 10.1371/journal.pone.0348571
PMID: 42224349
Database: MEDLINE
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