Ergatis: a web interface and scalable software system for bioinformatics workflows

Orvis, Joshua; Crabtree, Jonathan; Galens, Kevin; Gussman, Aaron; Inman, Jason M.; Lee, Eduardo; Nampally, Sreenath; Riley, David; Sundaram, Jaideep P.; Felix, Victor; Whitty, Brett; Mahurkar, Anup; Wortman, Jennifer; White, Owen; Angiuoli, Samuel V.

doi:10.1093/bioinformatics/btq167

DOE OSTI · 1625266

Ergatis: a web interface and scalable software system for bioinformatics workflows

Orvis, Joshua·Crabtree, Jonathan·Galens, Kevin·Gussman, Aaron·Inman, Jason M.·Lee, Eduardo·Nampally, Sreenath·Riley, David·Sundaram, Jaideep P.·Felix, Victor·Whitty, Brett·Mahurkar, Anup·Wortman, Jennifer·White, Owen·Angiuoli, Samuel V.

View original source ↗Read source document ↗Export metadata ↓

Abstract

Motivation: The growth of sequence data has been accompanied by an increasing need to analyze data on distributed computer clusters. The use of these systems for routine analysis requires scalable and robust software for data management of large datasets. Software is also needed to simplify data management and make large-scale bioinformatics analysis accessible and reproducible to a wide class of target users. Results: We have developed a workflow management system named Ergatis that enables users to build, execute and monitor pipelines for computational analysis of genomics data. Ergatis contains preconfigured components and template pipelines for a number of common bioinformatics tasks such as prokaryotic genome annotation and genome comparisons. Outputs from many of these components can be loaded into a Chado relational database. Ergatis was designed to be accessible to a broad class of users and provides a user friendly, web-based interface. Ergatis supports highthroughput batch processing on distributed compute clusters and has been used for data management in a number of genome annotation and comparative genomics projects.

Explore related subjects

59 BASIC BIOLOGICAL SCIENCES 97 MATHEMATICS AND COMPUTING Biochemistry & Molecular Biology Biotechnology & Applied Microbiology Computer Science Mathematical & Computational Biology Mathematics

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

Orvis, Joshua, Crabtree, Jonathan, Galens, Kevin, Gussman, Aaron, Inman, Jason M., Lee, Eduardo, Nampally, Sreenath, Riley, David, Sundaram, Jaideep P., Felix, Victor, Whitty, Brett, Mahurkar, Anup, Wortman, Jennifer, White, Owen, Angiuoli, Samuel V.. 2010-04-22. Ergatis: a web interface and scalable software system for bioinformatics workflows. https://doi.org/10.1093/bioinformatics%2Fbtq167

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related reports

DOE OSTI2026

Lines of Evidence Network Analysis of Yield-Associated Genes in Pennycress (Thlaspi arvense)

Functional network analysis of 112 GWAS-identified candidate genes for yield-related traits in pennycress ( Thlaspi arvense ). Uses RWRtools Lines of Evidence to propagate Arabidopsis orthologs through a nine-layer multiplex functional network.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

Soil metagenomics umbrella narrative

Implementing accessible, authentic research experiences in introductory courses is challenging, particularly at institutions serving diverse student populations. To address this gap, we developed and deployed a Course-based Undergraduate Research Experience (CURE) focused on plant-microbe interactions in General Biology II at Northeastern Illinois University (NEIU), a minority-serving institution with a diverse student body. Students grew sugar beets (Beta vulgaris), extracted DNA from the rhizoplane, and used the Department of Energy Systems Biology Knowledgebase (KBase) for bioinformatic analysis to compare microbial relative abundance in fertilized versus unfertilized soil. Over five semesters, the CURE engaged 103 students and leveraged the intuitive KBase platform to make complex sequencing data accessible. Pre/post-course survey data revealed significant increases in student self-assessed research skills, including the ability to explain results and determine the types of data to collect. Furthermore, students reported significant gains in confidence related to experimental design and hypothesis development, alongside a strong increase in familiarity with KBase. Informal faculty feedback indicated high student engagement and appreciation for the real-world connections (e.g. food systems, agriculture, and health). This scalable, low-cost model effectively integrates data science tools into the foundational curriculum, demonstrating a potent strategy for boosting research skills and broadening participation in authentic scientific inquiry among diverse undergraduate students.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

Genome-resolved insights into microbial diversity and elemental cycling in Winogradsky columns

We retained 18 MAGs with ≥50% completion and <10% contamination (i.e., at least medium quality). Of these, 10 had >90% completion and <5% contamination; however, only one (Paceibacteria Bin.003_MG) can be described as high-quality, as the others lacked a full suite of 5S, 16S, and 23S rRNA genes. To maximize the diversity of our recovered MAGs, we also retained one MAG (Chromatiaceae Bin.008_AM) with >40% (but less than 50%) completion and <5% contamination, as well as one (Rhodopseudomonas Bin.015_MK) with >90% completion and <20% (but>10%) contamination. Interestingly, significant chimerism was not detected in this MAG (40) , suggesting that the elevated contamination (20%) may instead reflect two closely related strains collapsing into a single bin. Consistent with this, contig coverage was bimodal, with roughly 17% of the assembly at ~115x and the remaining 83% at ~282x, while GC content remained uniform across both groups (~64%), arguing against contamination from a taxonomically distinct source.

59 BASIC BIOLOGICAL SCIENCES↗