FDA-ARGOS database updates may help researchers rapidly validate diagnostic tests and use qualified genetic sequences to support future product development
As of September 2021, Embleema and George Washington University have been conducting bioinformatic research and system development, focusing on expanding the FDA-ARGOS database. This project expands datasets publicly available in FDA-ARGOS, improves quality control by developing quality matrix tools and scoring approaches that will allow the mining of public sequence databases, and identifies high-quality sequences for upload to the FDA-ARGOS database as regulatory-grade sequences. Building on expansions during the COVID-19 pandemic, this project aims to further improve the utility of the FDA-ARGOS database as a key tool for medical countermeasure development and validation.
For additional details on project information and assembly QC see:
The Data Dictionary directory contains the controlled vocabulary and standardized definitions for ARGOS data tables.
Current version: v1.6.1
This resource was developed to support the integration of ARGOS data from multiple, disparate sources by ensuring a consistent representation of data properties across all datasets in ARGOS.
Each entry in the Data Dictionary corresponds to a column header used in data tables on data.argosdb.org, and includes:
- Standardized qc attribute (column) names
- Descriptions defining each data property
- Data types and expected formats
- Harmonized terminology across datasets
These terms were:
- Proposed by ARGOS project members and FDA collaborators
- Manually curated to merge overlapping or redundant fields
- Standardized to ensure consistency across all data tables
The primary purpose of the Data Dictionary is to:
- Ensure all data submitted to ARGOS follows a consistent and controlled structure
- Enable reliable integration of datasets from different sources
- Support accurate interpretation of QC metrics and biosample metadata
The Data Dictionary complements the schema directory: schema/
Data Dictionary → human-readable definitions and controlled vocabulary
The data_files folder contains archived and reference data tables used throughout the project, including materials from Release 1.0 (December 2025), older data table files, and other historical supporting files. It also includes HumanPathogens_Comprehensive.xlsx, an important reference table of human pathogenic organisms spanning bacteria, viruses, and eukaryotic pathogens, compiled from multiple curated sources for downstream analysis and database integration. The current dataset contains 1,705 bacterial species, 1,598 viral species, and 49 fungal and other eukaryotic organisms, and while the table can be reviewed on the wiki, the full file is also available in this repository for download and use.
The docs folder contains reference materials focused on lineage structure and overall data flow within the pipeline. These documents provide background context on how taxonomic relationships are organized and how data moves through the system. While helpful for understanding the framework, some content may be outdated compared to the current implementation.
The lib directory contains scripts and supporting code used for data retrieval, processing, and table generation within ARGOS workflows.
These scripts have been used to:
- Retrieve data and identifiers from external APIs (e.g., NCBI)
- Process and transform QC outputs
- Generate standardized data tables and supporting schema inputs
Subdirectories
- HIVE3/ Contains scripts used historically to generate ARGOS data tables using HIVE3-based QC workflows. Some scripts may be outdated due to ongoing changes and updates to HIVE3 over time.
- current/ Contains the actively maintained codebase used to generate the data tables currently available on data.argosdb.org. These scripts can also be adapted to generate custom tables from HIVE QC outputs.
- shell/ Contains legacy shell scripts that were used in earlier versions of the pipeline and are no longer actively maintained.
This directory contains the ARGOS data schemas, organized by release version. Each version defines the expected structure and validation rules for datasets published on ARGOS.
Current version: v1.6
What is included in each schema version?
Each version contains a core/ subdirectory, which houses JSON schema files corresponding to the data tables available on data.argosdb.org. There is an annotation/ subdirectory, but we are not currently performing any annotations.
These JSON schemas define:
- Column names (attributes) for each dataset
- Data types (e.g., string, integer, float)
- Descriptions explaining the meaning of each field
- Titles for readability and standardization
- Example values to guide interpretation and usage
This structure ensures consistency, transparency, and reproducibility across ARGOS datasets.
Example schema file:
Assume you wanted to validate a file of the typeSRA_ngsQC(this same process should work for any of the types we have defined).
- The data file is
/data_files/test_SRA_ngsQC.tsv - The schema for a
SRA_ngsQCdata file is/schema/v0.5/non-core/SRA_ngsQC.json
For illitstration purposes cell T6 in our example data file has been modified. The schema says that the value has to be less than 1, as gc_ content is a percentage. The example data sheet has a value of 10.63682374 in that cell, and the following error should be thrown:
Line 5 failed. '10.63682374' does not match '^[+-]?([0]+\\.?[0-9]*|\\.[0-9]+)$
From the project root run:
> python lib/dictionary_utils.py validate -i data_files/test_SRA_ngsQC.tsv -s schema/v0.5/non-core/SRA_ngsQC.jsonBoth the schema [-s] and input file [-i] values can take a URL, assuming they are formatted correctly and resolvable.
For Example:
> python lib/dictionary_utils.py validate -i https://raw.githubusercontent.com/FDA-ARGOS/data.argosdb/v0.5/data_files/test_SRA_ngsQC.tsv -s https://raw.githubusercontent.com/FDA-ARGOS/data.argosdb/v0.5/schema/v0.5/non-core/SRA_ngsQC.json
should give you the same results.
COVID-DRDB is created by the HIVDB team of Stanford University. It includes resistance data of SARS-CoV-2 for convalescent plasma, vaccinee plasma and monoclonal antibodies collected from published peer-reviewed/pre-print studies. The documents and files can be found here.
Sichtig, H., Minogue, T., Yan, Y. et al. FDA-ARGOS is a database with public quality-controlled reference genomes for diagnostic use and regulatory science. Nat Commun 10, 3313 (2019). https://doi.org/10.1038/s41467-019-11306-6