{"doi":"10.3389/fmicb.2023.1060891","title":"The K-mer antibiotic resistance gene variant analyzer (KARGVA)","abstract":"Characterization of antibiotic resistance genes (ARGs) from high-throughput sequencing data of metagenomics and cultured bacterial samples is a challenging task, with the need to account for both computational (e.g., string algorithms) and biological (e.g., gene transfers, rearrangements) aspects. Curated ARG databases exist together with assorted ARG classification approaches (e.g., database alignment, machine learning). Besides ARGs that naturally occur in bacterial strains or are acquired through mobile elements, there are chromosomal genes that can render a bacterium resistant to antibiotics through point mutations, i.e., ARG variants (ARGVs). While ARG repositories also collect ARGVs, there are only a few tools that are able to identify ARGVs from metagenomics and high throughput sequencing data, with a number of limitations (e.g., pre-assembly, a posteriori verification of mutations, or specification of species). In this work we present the k -mer, i.e., strings of fixed length k , ARGV analyzer – KARGVA – an open-source, multi-platform tool that provides: (i) an ad hoc , large ARGV database derived from multiple sources; (ii) input capability for various types of high-throughput sequencing data; (iii) a three-way, hash-based, k -mer search setup to process data efficiently, linking k -mers to ARGVs, k -mers to point mutations, and ARGVs to k -mers, respectively; (iv) a statistical filter on sequence classification to reduce type I and II errors. On semi-synthetic data, KARGVA provides very high accuracy even in presence of high sequencing errors or mutations (99.2 and 86.6% accuracy within 1 and 5% base change rates, respectively), and genome rearrangements (98.2% accuracy), with robust performance on ad hoc false positive sets. On data from the worldwide MetaSUB consortium, comprising 3,700+ metagenomics experiments, KARGVA identifies more ARGVs than Resistance Gene Identifier (4.8x) and PointFinder (6.8x), yet all predictions are below the expected false positive estimates. The prevalence of ARGVs is correlated to ARGs but ecological characteristics do not explain well ARGV variance. KARGVA is publicly available at https://github.com/DataIntellSystLab/KARGVA under MIT license.","journal":"Frontiers in Microbiology","year":2023,"id":369213,"datarank":0.4129795079943665,"base_score":2.3978952727983707,"endowment":2.3978952727983707,"self_citation_contribution":0.3596842909197557,"citation_network_contribution":0.053295217074610844,"self_endowment_contribution":0.3596842909197557,"citer_contribution":0.053295217074610844,"corpus_percentile":55.28738299682834,"corpus_rank":5781,"citation_count":10,"citer_count":6,"citers_with_citation_signal":4,"citers_with_endowment":4,"datacite_reuse_total":0,"is_dataset":true,"is_dataset_confidence":0.9317,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2023-01-01","fair_score":66.6667,"fair_percentile":86.48731274839498,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":23991,"name":"Christina Boucher","orcid":"0000-0001-9509-9725","position":1,"is_corresponding":false},{"id":23993,"name":"Noelle Noyes","orcid":"0000-0001-6149-1008","position":2,"is_corresponding":false},{"id":285001,"name":"Mattia Prosperi","orcid":"0000-0002-9021-5595","position":3,"is_corresponding":false},{"id":295646,"name":"Simone Marini","orcid":"0000-0002-5704-3533","position":0,"is_corresponding":true}],"reference_count":34,"raw_metadata":null,"created_at":"2026-07-19T01:15:28.704894Z","pmid":"36960290","pmcid":"PMC10027697","fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":38.8889,"fair_a":75.0,"fair_i":20.0,"fair_r":66.6667,"fair_zscore":1.2752,"fair_rationale":{"fair_score":66.67,"has_llm":true,"taxonomy_version":"fair_taxonomy_v5","dimensions":{"F":{"name":"Findable","score":38.89,"criteria":[{"key":"f_dataset_pid","label":"Persistent identifier for the data","kind":"llm","weight":2.0,"fraction":0.5,"verdict":"partial","evidence":"KARGVA is publicly available at https://github.com/DataIntellSystLab/KARGVA under MIT license.","grounded":true,"rationale":"The data are identified by a web URL (GitHub), not a persistent identifier scheme.","anchors":["RDA-F1-01D — FAIR Data Maturity Model: 'Data is identified by a persistent identifier' (priorit","RDA-F1-02D — FAIR Data Maturity Model: 'Data is identified by a globally unique identifier'","FsF-F1-02D — F-UJI/FAIRsFAIR: 'Data is assigned a persistent identifier'"],"scored":true,"signal":null},{"key":"f_repository_named","label":"Named repository","kind":"llm","weight":2.0,"fraction":0.5,"verdict":"partial","evidence":"KARGVA is publicly available at https://github.com/DataIntellSystLab/KARGVA under MIT license.","grounded":true,"rationale":"The data are hosted on GitHub, which is a code-hosting platform but not a curated data repository.","anchors":["RDA-F4-01M — FAIR Data Maturity Model: metadata is offered so it can be harvested and indexed (","NIH DMS Policy Element 4 (NOT-OD-21-014) — name the repository where data will be archived","NSTC Desirable Characteristics of Data Repositories (2022) — 'Long-Term Sustainability', 'Reten"],"scored":true,"signal":null},{"key":"f_data_availability_statement","label":"Data-availability statement","kind":"llm","weight":2.0,"fraction":0.5,"verdict":"partial","evidence":"KARGVA code can be found here: https://github.com/DataIntellSystLab/KARGVA","grounded":false,"rationale":"The data availability statement points to a public repository (GitHub) with a direct link to the code, which is a persistent link to archived data in a public repository. 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[downgraded to 'no' — no verifiable quote from the paper]","anchors":["RDA-F2-01M — 'Rich metadata is provided to allow discovery' (priority Essential)","FsF-F2-01M — F-UJI: 'Metadata includes descriptive core elements to support data findability'","FsF-R1-01MD — F-UJI: 'Metadata specifies the content of the data'"],"scored":false,"signal":null},{"key":"f_dataset_cited","label":"Dataset formally cited","kind":"llm","weight":1.0,"fraction":0.5,"verdict":"partial","evidence":"KARGVA is publicly available at https://github.com/DataIntellSystLab/KARGVA under MIT license.","grounded":true,"rationale":"The dataset identifier (GitHub URL) appears only in body text, not in the reference list. [majority verdict 'partial' (4/5 passes agreed)]","anchors":["FORCE11 Joint Declaration of Data Citation Principles (2014) — data should be cited as a first-","RDA-F3-01M — metadata clearly and explicitly includes the identifier of the data it describes","FsF-F3-01M — F-UJI: 'Metadata includes the identifier of the data it describes'"],"scored":true,"signal":null}]},"A":{"name":"Accessible","score":75.0,"criteria":[{"key":"a_data_openly_accessible","label":"Access route free of preconditions","kind":"llm","weight":2.0,"fraction":1.0,"verdict":"yes","evidence":"KARGVA is publicly available at https://github.com/DataIntellSystLab/KARGVA under MIT license.","grounded":true,"rationale":"The text gives a route to the data with no stated precondition; it is open and freely available.","anchors":["RDA-A1.1-01D — 'Data is accessible through a free access protocol'","FsF-A1-01M — F-UJI: 'Metadata contains access level and access conditions of the data'","NSTC Desirable Characteristics of Data Repositories (2022) — 'Free and Easy Access'"],"scored":true,"signal":null},{"key":"a_access_conditions_stated","label":"Access level labelled","kind":"llm","weight":1.0,"fraction":1.0,"verdict":"yes","evidence":"KARGVA is publicly available at https://github.com/DataIntellSystLab/KARGVA under MIT license.","grounded":true,"rationale":"The paper labels the data as 'publicly available', a natural-language equivalent of 'open access'.","anchors":["FsF-A1-01M — F-UJI: 'Metadata contains access level and access conditions of the data'","RDA-A1-01M — metadata contains information to enable the user to get access to the data","COAR Controlled Vocabularies — Access Rights v1.0 (open / embargoed / restricted / metadata-onl"],"scored":false,"signal":null},{"key":"a_controlled_access_for_sensitive","label":"Gatekeeper for sensitive data","kind":"llm","weight":0.5,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"The data are not sensitive human-subject data; no gatekeeper is named.","anchors":["NIH Genomic Data Sharing Policy (NOT-OD-14-124) — controlled-access via a Data Access Committee","RDA-A1.2-01D — 'Data is accessible through an access protocol that supports authentication and ","NIH DMS Policy Element 5 (NOT-OD-21-014) — Access, Distribution, or Reuse Considerations (conse"],"scored":false,"signal":null},{"key":"a_timeline_retention","label":"Availability timing & retention","kind":"llm","weight":0.5,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"No sentence states how long the data will remain available or a persistence commitment. [majority verdict 'no' (3/5 passes agreed)]","anchors":["NIH DMS Plan Element 4 (NOT-OD-21-014) — Data Preservation, Access, and Associated Timelines","NSTC Desirable Characteristics (2022), Organizational Infrastructure: 'Retention Policy'","RDA-A2-01M — 'Metadata is guaranteed to remain available after data is no longer available'"],"scored":false,"signal":null}]},"I":{"name":"Interoperable","score":20.0,"criteria":[{"key":"i_open_nonproprietary_format","label":"Open file format","kind":"llm","weight":1.0,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"No file format for the released data is named anywhere in the text.","anchors":["FsF-R1.3-02D — F-UJI: 'Data is available in a file format recommended by the target research co","RDA-R1.3-02D — data is expressed in a machine-understandable community standard","RDA-I1-01D — data uses a knowledge representation expressed in a standardised format"],"scored":true,"signal":null},{"key":"i_community_standard_vocabulary","label":"Community standard / vocabulary","kind":"llm","weight":1.0,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"No community standard (e.g., MIAME, MIxS, an ontology) is named as applied to the data.","anchors":["RDA-R1.3-01M — 'Metadata complies with a community standard' (priority Essential)","RDA-R1.3-01D — 'Data complies with a community standard'","RDA-I2-01M — '(Meta)data use vocabularies that follow FAIR principles'"],"scored":false,"signal":null},{"key":"i_qualified_references","label":"Identifiers for the resources the data depend on","kind":"llm","weight":0.5,"fraction":1.0,"verdict":"yes","evidence":"MEGARes 2.0 can be found here: https://www.meglab.org/megares/download/.","grounded":true,"rationale":"The paper gives a URL identifier for the MEGARes database, a resource other than its own data. [majority verdict 'yes' (4/5 passes agreed)]","anchors":["RDA-I3-01M — '(meta)data include references to other (meta)data'","RDA-I3-03M — 'metadata includes qualified references to other metadata'","FsF-I3-01M — F-UJI: 'Metadata includes links between the data and its related entities'"],"scored":false,"signal":null}]},"R":{"name":"Reusable","score":66.67,"criteria":[{"key":"r_reuse_license","label":"Reuse licence","kind":"llm","weight":2.0,"fraction":1.0,"verdict":"yes","evidence":"KARGVA is publicly available at https://github.com/DataIntellSystLab/KARGVA under MIT license.","grounded":true,"rationale":"The MIT license is an open standard license, fulfilling class 1.","anchors":["RDA-R1.1-01M — 'Metadata includes information about the licence under which the data can be reu","RDA-R1.1-02M — 'Metadata refers to a standard reuse licence'","RDA-R1.1-03M — 'Metadata refers to a machine-understandable reuse licence'"],"scored":true,"signal":null},{"key":"r_provenance_methods","label":"Provenance of the data","kind":"llm","weight":1.0,"fraction":0.0,"verdict":"no","evidence":"KARGV A integrates ARGV sequences from three different ARG databases: CARD, MEGARes, and NDARO.","grounded":false,"rationale":"The data production is described in generic terms without naming specific instruments or kits. [downgraded to 'no' — no verifiable quote from the paper] [majority verdict 'no' (4/5 passes agreed)]","anchors":["RDA-R1.2-01M — 'Metadata includes provenance information according to community- specific standa","FsF-R1.2-01M — F-UJI: 'Metadata includes provenance information about data creation or generati","W3C PROV-O (W3C Recommendation, 2013) — the entity/activity/agent model of provenance"],"scored":false,"signal":null},{"key":"r_documentation_codebook","label":"Documentation / codebook","kind":"llm","weight":1.0,"fraction":0.5,"verdict":"partial","evidence":"The GitHub folder includes a detailed README with information about database version, set up of input parameters (k-mer length, number of random queries to determine false positive threshold, ARGV reference file, read file, single vs. multiple ARGV scoring per read), and output file description.","grounded":false,"rationale":"A README file is named as travelling with the data, providing documentation. [downgraded to 'partial' — no verifiable quote from the paper] [majority verdict 'partial' (4/5 passes agreed)]","anchors":["RDA-R1-01M — '(Meta)data are richly described with a plurality of accurate and relevant attribu","FsF-R1-01MD — F-UJI: 'Metadata specifies the content of the data'","NIH DMS Policy Element 3 (NOT-OD-21-014) — Standards (documentation and metadata to accompany t"],"scored":false,"signal":null},{"key":"r_versioning","label":"Snapshot identified","kind":"llm","weight":0.5,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"No version token or date is given for the released data snapshot.","anchors":["DataCite Metadata Schema 4.6 — the 'Version' property","RDA-R1.2-01M — provenance information (which version was used is provenance)","NSTC Desirable Characteristics of Data Repositories (2022) — 'Provenance', 'Retention Policy'"],"scored":true,"signal":null},{"key":"x_code_availability","label":"Analysis code available","kind":"llm","weight":1.0,"fraction":1.0,"verdict":"yes","evidence":"KARGVA is publicly available at https://github.com/DataIntellSystLab/KARGVA under MIT license.","grounded":true,"rationale":"A machine-resolvable code repository URL is given for the study's own code.","anchors":["NIH DMS Policy Element 2 (NOT-OD-21-014) — 'Related Tools, Software and/or Code'","FAIR4RS Principles v1.0 (Chue Hong et al., 2022; RDA/FORCE11/ReSA) — FAIR Principles for Resear","FORCE11 Software Citation Principles (Smith, Katz & Niemeyer, 2016, PeerJ CS 2:e86)"],"scored":true,"signal":null},{"key":"x_funding_attribution","label":"Funder and award number","kind":"llm","weight":0.5,"fraction":1.0,"verdict":"yes","evidence":"This work was in part supported by US grants NIH NIAID R01AI141810, NSF SCH 2013998, and USDA AFRI 2019-67017-29110.","grounded":true,"rationale":"Award numbers are provided for the funders.","anchors":["DataCite Metadata Schema 4.6 — 'FundingReference' property (funderName, funderIdentifier, award","Crossref Funder Registry — canonical funder identifiers for funding metadata","RDA-F2-01M — rich metadata provided to allow discovery (funding is part of the descriptive reco"],"scored":true,"signal":null}]}},"actions":[{"key":"f_dataset_pid","dimension":"F","label":"Persistent identifier for the data","action":"Mint or cite a persistent identifier for the dataset — a repository DOI or an accession from a registered repository — and print it in the paper. A bare URL is not persistent: it is the single most common cause of a dead data link five years after publication. For clinical / human-subjects data, deposit in dbGaP or the European Genome-phenome Archive (EGA).","anchors":["yes","partial","no"],"verdict":"partial","current":0.5,"evidence":"KARGVA is publicly available at https://github.com/DataIntellSystLab/KARGVA under MIT license.","why":"The data are identified by a web URL (GitHub), not a persistent identifier scheme.","gain":8.33,"priority":"essential","scored":true},{"key":"f_repository_named","dimension":"F","label":"Named repository","action":"Deposit the data in a repository registered in re3data/FAIRsharing (a domain repository such as GEO, SRA, dbGaP, PRIDE, or a generalist such as Zenodo, Dryad, Dataverse) and name it explicitly in the paper. A lab website is not an archive: it has no retention commitment and no accession. For clinical / human-subjects data, deposit in dbGaP or the European Genome-phenome Archive (EGA).","anchors":["yes","partial","no"],"verdict":"partial","current":0.5,"evidence":"KARGVA is publicly available at https://github.com/DataIntellSystLab/KARGVA under MIT license.","why":"The data are hosted on GitHub, which is a code-hosting platform but not a curated data repository.","gain":8.33,"priority":"essential","scored":true},{"key":"i_open_nonproprietary_format","dimension":"I","label":"Open file format","action":"Release the data in an open, community-standard format (CSV/TSV, JSON, HDF5, NetCDF, FASTQ, VCF, NIfTI…) instead of — or alongside — any proprietary or instrument-native format, and name the format in the paper. A dataset that needs a €2,000 licence to open is not reusable.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"No file format for the released data is named anywhere in the text.","gain":8.33,"priority":"important","scored":true},{"key":"f_dataset_cited","dimension":"F","label":"Dataset formally cited","action":"Cite the dataset in the reference list like a publication — creator, year, title, repository, DOI/accession — and cite it in-text where it is used. Only a reference- list entry is machine-readable to Crossref/DataCite, and only a citation lets the data earn credit. Cite the clinical / human-subjects repository accession (e.g. from dbGaP or the European Genome-phenome Archive (EGA)) in the reference list.","anchors":["yes","partial","no"],"verdict":"partial","current":0.5,"evidence":"KARGVA is publicly available at https://github.com/DataIntellSystLab/KARGVA under MIT license.","why":"The dataset identifier (GitHub URL) appears only in body text, not in the reference list. [majority verdict 'partial' (4/5 passes agreed)]","gain":4.17,"priority":"important","scored":true},{"key":"r_versioning","dimension":"R","label":"Snapshot identified","action":"Version the deposit and cite the exact version analysed (a version-specific DOI, or an accession with its version suffix). A reader reproducing your work against 'the current release' is reproducing it against a different dataset.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"No version token or date is given for the released data snapshot.","gain":4.17,"priority":"useful","scored":true},{"key":"f_data_availability_statement","dimension":"F","label":"Data-availability statement","action":"Replace the statement with the repository template: name the repository and give the accession or DOI (Colavizza category 3). This is the only DAS class associated with a measured citation advantage; 'available on reasonable request' and 'within the article' are not.","anchors":["yes","partial","no"],"verdict":"partial","current":0.5,"evidence":"KARGVA code can be found here: https://github.com/DataIntellSystLab/KARGVA","why":"The data availability statement points to a public repository (GitHub) with a direct link to the code, which is a persistent link to archived data in a public repository. [downgraded to 'partial' — no verifiable quote from the paper] [majority verdict 'partial' (2/5 passes agreed)]","gain":0.0,"priority":"essential","scored":false},{"key":"f_discovery_metadata","dimension":"F","label":"Description of the dataset as an object","action":"Add a 'Data Records' section: itemise every file in the deposit and every variable or sample it holds, with counts and units. Describe the dataset as an object in its own right, not as a by-product of the findings — this is what makes it discoverable to someone who is not looking for your paper.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":"The KARGV A ARGV database integrates 1,159 single-point, and 95 multiple-point ARGVs from CARD (January 2021 release); and 654 single-point ARGVs from NDARO 3.10, respectively... After merging identical sequences, the final KARGV A database includes 1,781 ARGVs.","why":"The dataset's content is described in running prose, not in an itemised inventory section or table. [downgraded to 'no' — no verifiable quote from the paper]","gain":0.0,"priority":"essential","scored":false},{"key":"i_community_standard_vocabulary","dimension":"I","label":"Community standard / vocabulary","action":"Adopt and NAME your domain's data standard — the minimum-information checklist, metadata schema, or ontology your community uses (MIAME/MINSEQE, ISA-Tab, BIDS, an OBO ontology, HL7 FHIR/OMOP) — and say which one you followed. A reporting checklist standardises your paper; it does nothing for your data. In clinical / human-subjects, describe the data with OMOP CDM, CDISC SDTM or HL7 FHIR.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"No community standard (e.g., MIAME, MIxS, an ontology) is named as applied to the data.","gain":0.0,"priority":"important","scored":false},{"key":"r_provenance_methods","dimension":"R","label":"Provenance of the data","action":"Name the instruments, kits, and software — with versions — that produced the data, not just the verbs. 'Reads were aligned' is not provenance; 'aligned with STAR v2.7.9a to GRCh38' is, because someone else can rerun it.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":"KARGV A integrates ARGV sequences from three different ARG databases: CARD, MEGARes, and NDARO.","why":"The data production is described in generic terms without naming specific instruments or kits. [downgraded to 'no' — no verifiable quote from the paper] [majority verdict 'no' (4/5 passes agreed)]","gain":0.0,"priority":"important","scored":false},{"key":"r_documentation_codebook","dimension":"R","label":"Documentation / codebook","action":"Ship a README and a data dictionary IN the deposit — every file, every variable, its units, its allowed values, its missing-value codes. It is the cheapest single thing that makes a dataset usable by someone who was not in the lab, and a table buried in the article does not travel with the data.","anchors":["yes","partial","no"],"verdict":"partial","current":0.5,"evidence":"The GitHub folder includes a detailed README with information about database version, set up of input parameters (k-mer length, number of random queries to determine false positive threshold, ARGV reference file, read file, single vs. multiple ARGV scoring per read), and output file description.","why":"A README file is named as travelling with the data, providing documentation. [downgraded to 'partial' — no verifiable quote from the paper] [majority verdict 'partial' (4/5 passes agreed)]","gain":0.0,"priority":"important","scored":false},{"key":"a_controlled_access_for_sensitive","dimension":"A","label":"Gatekeeper for sensitive data","action":"Route sensitive data through an institutional gatekeeper — deposit in a controlled- access repository (dbGaP, EGA) with a Data Access Committee and a published DUA — rather than through the corresponding author's inbox. An author-gated dataset dies with the author's email address, and 'on reasonable request' has been shown repeatedly not to yield data. For sensitive/human clinical / human-subjects data, use a controlled-access repository such as dbGaP or EGA.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"The data are not sensitive human-subject data; no gatekeeper is named.","gain":0.0,"priority":"useful","scored":false},{"key":"a_timeline_retention","dimension":"A","label":"Availability timing & retention","action":"State when the data become available AND how long they will be retained — cite the repository's preservation policy. NIH DMS Element 4 asks for both; most papers give neither.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"No sentence states how long the data will remain available or a persistence commitment. [majority verdict 'no' (3/5 passes agreed)]","gain":0.0,"priority":"useful","scored":false}],"suggestions":["Mint or cite a persistent identifier for the dataset — a repository DOI or an accession from a registered repository — and print it in the paper. A bare URL is not persistent: it is the single most common cause of a dead data link five years after publication. For clinical / human-subjects data, deposit in dbGaP or the European Genome-phenome Archive (EGA).","Deposit the data in a repository registered in re3data/FAIRsharing (a domain repository such as GEO, SRA, dbGaP, PRIDE, or a generalist such as Zenodo, Dryad, Dataverse) and name it explicitly in the paper. A lab website is not an archive: it has no retention commitment and no accession. For clinical / human-subjects data, deposit in dbGaP or the European Genome-phenome Archive (EGA).","Release the data in an open, community-standard format (CSV/TSV, JSON, HDF5, NetCDF, FASTQ, VCF, NIfTI…) instead of — or alongside — any proprietary or instrument-native format, and name the format in the paper. A dataset that needs a €2,000 licence to open is not reusable.","Cite the dataset in the reference list like a publication — creator, year, title, repository, DOI/accession — and cite it in-text where it is used. Only a reference- list entry is machine-readable to Crossref/DataCite, and only a citation lets the data earn credit. Cite the clinical / human-subjects repository accession (e.g. from dbGaP or the European Genome-phenome Archive (EGA)) in the reference list.","Version the deposit and cite the exact version analysed (a version-specific DOI, or an accession with its version suffix). A reader reproducing your work against 'the current release' is reproducing it against a different dataset."],"model":"deepseek/deepseek-v4-flash","agent_version":"fair_agent_v8","fulltext_source":"unpaywall_pdf"},"fair_model":"deepseek/deepseek-v4-flash","fair_agent_version":"fair_agent_v8","fair_fulltext_source":"unpaywall_pdf","fair_has_llm":true,"fair_computed_at":"2026-07-20T12:28:30.481774Z","clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}