Omics Metadata Management Software (OMMS)

Abstract

Next-generation sequencing projects have underappreciated information management tasks requiring detailed attention to specimen curation, nucleic acid sample preparation and sequence production methods required for downstream data processing, comparison, interpretation, sharing and reuse. The few existing metadata management tools for genome-based studies provide weak curatorial frameworks for experimentalists to store and manage idiosyncratic, project-specific information, typically offering no automation supporting unified naming and numbering conventions for sequencing production environments that routinely deal with hundreds, if not thousands of samples at a time. Moreover, existing tools are not readily interfaced with bioinformatics executables, (e.g., BLAST, Bowtie2, custom pipelines). Our application, the Omics Metadata Management Software (OMMS), answers both needs, empowering experimentalists to generate intuitive, consistent metadata, and perform analyses and information management tasks via an intuitive web-based interface. Several use cases with short-read sequence datasets are provided to validate installation and integrated function, and suggest possible methodological road maps for prospective users. Provided examples highlight possible OMMS workflows for metadata curation, multistep analyses, and results management and downloading. The OMMS can be implemented as a stand alone-package for individual laboratories, or can be configured for webbased deployment supporting geographically-dispersed projects. The OMMS was developed using an open-source software base, is flexible, extensible and easily installed and executed. The OMMS can be obtained at http://omms.sandia.gov.AvailabilityThe OMMS can be obtained at http://omms.sandia.gov

The IsoGenie database: an interdisciplinary data management solution for ecosystems biology and environmental research

“…However, they do not integrate their data in a framework that allows scalable and detailed querying (e.g., quickly extracting all water table and temperature data from multiple sites into a single table, for scaling of water table-temperature relationships from individual sites to a broader geographical range). The field of bioinformatics is further along in this regard: for molecular meta-omic data, numerous databases (e.g., MIGS/MIMS, MIMAS, IMG/M, GeneLab) (Hermida et al, 2006;Field et al, 2008;Gattiker et al, 2009;Chen et al, 2019;Ray et al, 2019) and integrative data management platforms (e.g., KBase, MOD-CO, ODG, GeNNet, BioKNO, MGV, OMMS, mixOmics) (Sujansky, 2001;Symons & Nieselt, 2011;Perez-Arriaga et al, 2015;Yoon, Kim & Kim, 2017;Costa et al, 2017;Rohart et al, 2017;Guhlin et al, 2017;Manzoni et al, 2018;Arkin et al, 2018;Brandizi et al, 2018;Rambold et al, 2019) have been developed, and often include standardization of sample metadata to enable efficient data integration. Notable among these are KBase (https://kbase.us/) (Arkin et al, 2018), which provides "apps" through which users can process their data in a framework that tracks processing steps ("provenance") in an accessible format, and MOD-CO (Rambold et al, 2019), a bioinformatics data processing tool that includes a conceptual schema and data model to track metadata and workflows.…”

Peer Review #1 of "The IsoGenie database: an interdisciplinary data management solution for ecosystems biology and environmental research (v0.2)"

“…However, they do not integrate their data in a framework that allows scalable and detailed querying (for example, quickly extracting all water table and temperature data from multiple sites into a single table, for scaling of water table-temperature relationships from individual sites to a broader geographical range). The field of bioinformatics is further along in this regard: for molecular meta-omic data, numerous databases (e.g., MIGS/MIMS, MIMAS, IMG/M, GeneLab) (Hermida et al, 2006;Field et al, 2008;Gattiker et al, 2009;Chen et al, 2019;Ray et al, 2019) and integrative data management platforms (e.g., KBase, MOD-CO, ODG, GeNNet, BioKNO, MGV, OMMS, mixOmics) (Sujansky, 2001;Symons & Nieselt, 2011;Perez-Arriaga et al, 2015;Yoon, Kim & Kim, 2017;Costa et al, 2017;Rohart et al, 2017;Guhlin et al, 2017;Manzoni et al, 2018;Arkin et al, 2018;Brandizi et al, 2018;Rambold et al, 2019) have been developed, and often include standardization of sample metadata to enable efficient data integration. Notable among these are KBase (https://kbase.us/) (Arkin et al, 2018), which provides "apps" through which users can process their data in a framework that tracks processing steps ("provenance") in an accessible format, and MOD-CO (Rambold et al, PeerJ reviewing PDF | (2019:10:42335:1:1:NEW 22 May 2020)…”