{"doi":"10.1002/em.70034","title":"Identifying Gene Predictors of Chemicals Linked With Breast Cancer: A Machine Learning Analysis of <scp>MCF7</scp> Cellular Transcriptomic Screening Data","abstract":"Breast cancer is the most prevalent cancer in women and has been linked to exposure to environmental chemicals. However, many chemicals have not been evaluated for relationships with this outcome. In this study, we analyzed RNA sequencing data from human breast cancer-derived MCF7 cells exposed to hundreds of individual chemicals. These chemicals were binned into three categories: (1) chemicals with known associations to breast cancer (BCs); (2) chemicals with a lack of relationship to breast cancer (NBCs); and (3) chemicals that remain understudied for breast cancer risk (UCs). Machine learning models were trained to discriminate between BCs and NBCs based on transcriptomic and physicochemical property data. The best model yielded a balanced accuracy of 80% and was applied to the UCs. A total of 170 genes were found to contribute to model performance, including Claspin (CLSPN), Runt-related Transcription Factor 2 (RUNX2), and Ubinuclein 2 (UBN2). These genes further informed enriched pathways relevant to inflammation, ferroptosis signaling, and cell proliferation. Additionally, 97 UCs were predicted to be more analogous to BCs, including select biocides and dyes. To ground results in human population data, expression profiles for the 170 genes were assessed in tumor samples from The Cancer Genome Atlas, yielding overlap in human cancer-relevant alterations and in vitro chemical-induced alterations. Collectively, this study addresses a gap related to understanding which chemicals may be of interest for further characterization of breast cancer risk by prioritizing chemicals and underlying mechanisms using high-throughput transcriptomic screening data.","journal":"Environmental and Molecular Mutagenesis","year":2025,"id":574728,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":0.0,"corpus_rank":10062,"citation_count":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":true,"is_dataset_confidence":0.7228,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":66.6667,"fair_percentile":86.48731274839498,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":87739,"name":"Richard Judson","orcid":"0000-0002-2348-9633","position":1,"is_corresponding":false},{"id":373418,"name":"Julia E. Rager","orcid":"0000-0002-2882-5042","position":2,"is_corresponding":false},{"id":888194,"name":"Lauren E. Koval","orcid":"0000-0001-5582-9383","position":0,"is_corresponding":true}],"reference_count":92,"raw_metadata":null,"created_at":"2026-07-19T02:57:44.572630Z","pmid":"40936337","pmcid":"PMC12574692","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":66.6667,"fair_a":81.25,"fair_i":20.0,"fair_r":41.6667,"fair_zscore":1.2752,"fair_rationale":{"fair_score":66.67,"has_llm":true,"taxonomy_version":"fair_taxonomy_v5","dimensions":{"F":{"name":"Findable","score":66.67,"criteria":[{"key":"f_dataset_pid","label":"Persistent identifier for the data","kind":"llm","weight":2.0,"fraction":1.0,"verdict":"yes","evidence":"GSE272548","grounded":true,"rationale":"The paper gives a GEO accession (GSE272548), which is a persistent identifier scheme. [majority verdict 'yes' (3/5 passes agreed)]","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":1.0,"verdict":"yes","evidence":"FASTQ files and aligned counts have been deposited in the NCBI Gene Expression Omnibus","grounded":true,"rationale":"The NCBI Gene Expression Omnibus (GEO) is a named data repository. [majority verdict 'yes' (4/5 passes agreed)]","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":"All data, analysis scripts, and results from this analysis are publicly available. Analysis scripts, datasets and results are organized on the Rager lab Github site (https://github.com/Ragerlab). FASTQ files and aligned counts have been deposited in the NCBI Gene Expression Omnibus (https://www.ncbi.nlm.nih.gov/geo/) with accession number GSE272548.","grounded":false,"rationale":"The statement points to a repository (GEO) with an accession number, matching Colavizza category 3. [downgraded to 'partial' — no verifiable quote from the paper] [majority verdict 'partial' (3/5 passes agreed)]","anchors":["Colavizza, Hrynaszkiewicz, Staden, Whitaker & McGillivray (2020), 'The citation advantage of li","Springer Nature research data policy — Data Availability Statements: standard statement templat","RDA-F3-01M — metadata clearly and explicitly includes the identifier of the data it describes"],"scored":false,"signal":null},{"key":"f_discovery_metadata","label":"Description of the dataset as an object","kind":"llm","weight":2.0,"fraction":0.5,"verdict":"partial","evidence":"A full list of chemicals and classifications can be found in Table S1. ssAUC values for the 200 chemicals used in the machine learning analysis are shown in Table S2, and complete physicochemical property predictions can be found in Table S3.","grounded":false,"rationale":"The paper directs the reader to supplementary tables that itemise the dataset, constituting an itemised inventory. [downgraded to 'partial' — no verifiable quote from the paper] [majority verdict 'partial' (3/5 passes agreed)]","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":0.0,"verdict":"no","evidence":"FASTQ files and aligned counts have been deposited in the NCBI Gene Expression Omnibus (https://www.ncbi.nlm.nih.gov/geo/) with accession number GSE272548.","grounded":false,"rationale":"The dataset identifier appears only in the body text (Data Availability Statement), not in the reference list. [downgraded to 'no' — no verifiable quote from the paper] [majority verdict 'no' (3/5 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":81.25,"criteria":[{"key":"a_data_openly_accessible","label":"Access route free of preconditions","kind":"llm","weight":2.0,"fraction":1.0,"verdict":"yes","evidence":"All data, analysis scripts, and results from this analysis are publicly available.","grounded":true,"rationale":"The text states the data are publicly available at a repository with no precondition.","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":"All data, analysis scripts, and results from this analysis are publicly available.","grounded":true,"rationale":"The paper explicitly labels the data as 'publicly available', which is a natural-language synonym for 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 study generated cell-line data, not human-subject data; no gatekeeper is named or needed.","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":0.5,"verdict":"partial","evidence":"All data, analysis scripts, and results from this analysis are publicly available.","grounded":true,"rationale":"The paper says the data are available now but makes no statement about how long they will persist. [majority verdict 'partial' (4/5 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":0.5,"verdict":"partial","evidence":"FASTQ","grounded":false,"rationale":"The paper names FASTQ as the file format for the raw sequencing data, which is an open, community-standard format. [downgraded to 'partial' — no verifiable quote from the paper] [majority verdict 'partial' (3/5 passes agreed)]","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 checklist, schema, or ontology is named for the data; only tools and databases are referenced.","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":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"The paper does not provide an identifier (accession/DOI) for any external resource that the data depend on; it only cites publications.","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":41.67,"criteria":[{"key":"r_reuse_license","label":"Reuse licence","kind":"llm","weight":2.0,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"No licence is explicitly attached to the data; the CC BY-NC-ND licence applies to the article, not the dataset.","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":1.0,"verdict":"yes","evidence":"MCF7 cell lysates were analyzed using a custom-attenuated version of the TempO-Seq human whole transcriptome version 1 assay by BioSpyder","grounded":true,"rationale":"The paper names the specific assay (TempO-Seq) and platform (BioSpyder) used to generate the data. [majority verdict 'yes' (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":0.0,"verdict":"no","evidence":"A full list of chemicals and classifications can be found in Table S1. ssAUC values for the 200 chemicals used in the machine learning analysis are shown in Table S2, and complete physicochemical property predictions can be found in Table S3.","grounded":false,"rationale":"Variable and file definitions are provided inside the article as supplementary tables, not as a separate documentation object shipped with the data. [downgraded to 'no' — no verifiable quote from the paper] [majority verdict 'no' (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":"The paper provides no version token or date for the snapshot of the data; the GEO accession is not a version statement.","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":"https://github.com/Ragerlab","grounded":true,"rationale":"A machine-resolvable code repository URL (GitHub) is given for the analysis scripts. [majority verdict 'yes' (3/5 passes agreed)]","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 supported by National Institutes of Health, T32ES007018; National Institute of Environmental Health Sciences, P30ES010126.","grounded":true,"rationale":"The paper provides specific grant numbers for the funding sources.","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":"r_reuse_license","dimension":"R","label":"Reuse licence","action":"Attach a standard, machine-readable open licence to the deposit — CC0 or CC BY, which is what Horizon Europe and most funders expect — and print the licence identifier in the paper. 'Free to use' is not a licence: it grants nothing a reuser's institution can rely on.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"No licence is explicitly attached to the data; the CC BY-NC-ND licence applies to the article, not the dataset.","gain":16.67,"priority":"essential","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 genomics / sequencing repository accession (e.g. from GEO (GSE accession), SRA (SRP/SRR) or ENA/BioProject (PRJEB/PRJNA)) in the reference list.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":"FASTQ files and aligned counts have been deposited in the NCBI Gene Expression Omnibus (https://www.ncbi.nlm.nih.gov/geo/) with accession number GSE272548.","why":"The dataset identifier appears only in the body text (Data Availability Statement), not in the reference list. [downgraded to 'no' — no verifiable quote from the paper] [majority verdict 'no' (3/5 passes agreed)]","gain":8.33,"priority":"important","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. Prefer open genomics / sequencing formats such as FASTQ, BAM or VCF.","anchors":["yes","partial","no"],"verdict":"partial","current":0.5,"evidence":"FASTQ","why":"The paper names FASTQ as the file format for the raw sequencing data, which is an open, community-standard format. [downgraded to 'partial' — no verifiable quote from the paper] [majority verdict 'partial' (3/5 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":"The paper provides no version token or date for the snapshot of the data; the GEO accession is not a version statement.","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":"All data, analysis scripts, and results from this analysis are publicly available. Analysis scripts, datasets and results are organized on the Rager lab Github site (https://github.com/Ragerlab). FASTQ files and aligned counts have been deposited in the NCBI Gene Expression Omnibus (https://www.ncbi.nlm.nih.gov/geo/) with accession number GSE272548.","why":"The statement points to a repository (GEO) with an accession number, matching Colavizza category 3. [downgraded to 'partial' — no verifiable quote from the paper] [majority verdict 'partial' (3/5 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":"partial","current":0.5,"evidence":"A full list of chemicals and classifications can be found in Table S1. ssAUC values for the 200 chemicals used in the machine learning analysis are shown in Table S2, and complete physicochemical property predictions can be found in Table S3.","why":"The paper directs the reader to supplementary tables that itemise the dataset, constituting an itemised inventory. [downgraded to 'partial' — no verifiable quote from the paper] [majority verdict 'partial' (3/5 passes agreed)]","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 genomics / sequencing, describe the data with MIAME, MINSEQE or MIxS.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"No community-standard checklist, schema, or ontology is named for the data; only tools and databases are referenced.","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":"no","current":0.0,"evidence":"A full list of chemicals and classifications can be found in Table S1. ssAUC values for the 200 chemicals used in the machine learning analysis are shown in Table S2, and complete physicochemical property predictions can be found in Table S3.","why":"Variable and file definitions are provided inside the article as supplementary tables, not as a separate documentation object shipped with the data. [downgraded to 'no' — no verifiable quote from the paper] [majority verdict 'no' (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 genomics / sequencing data, use a controlled-access repository such as dbGaP or EGA.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"The study generated cell-line data, not human-subject data; no gatekeeper is named or needed.","gain":0.0,"priority":"useful","scored":false},{"key":"i_qualified_references","dimension":"I","label":"Identifiers for the resources the data depend on","action":"Cite by identifier every resource the data depend on — the source datasets' accessions, the reference build (GRCh38 / GCA_000001405.28), the cohort application number, the code DOI — and register those relations on the dataset record (IsDerivedFrom, IsSupplementTo). A name is not a link: it cannot be resolved, versioned, or followed by a machine.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"The paper does not provide an identifier (accession/DOI) for any external resource that the data depend on; it only cites publications.","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":"partial","current":0.5,"evidence":"All data, analysis scripts, and results from this analysis are publicly available.","why":"The paper says the data are available now but makes no statement about how long they will persist. [majority verdict 'partial' (4/5 passes agreed)]","gain":0.0,"priority":"useful","scored":false}],"suggestions":["Attach a standard, machine-readable open licence to the deposit — CC0 or CC BY, which is what Horizon Europe and most funders expect — and print the licence identifier in the paper. 'Free to use' is not a licence: it grants nothing a reuser's institution can rely on.","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 genomics / sequencing repository accession (e.g. from GEO (GSE accession), SRA (SRP/SRR) or ENA/BioProject (PRJEB/PRJNA)) in the reference list.","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. Prefer open genomics / sequencing formats such as FASTQ, BAM or VCF.","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.","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."],"model":"deepseek/deepseek-v4-flash","agent_version":"fair_agent_v8","fulltext_source":"epmc_xml"},"fair_model":"deepseek/deepseek-v4-flash","fair_agent_version":"fair_agent_v8","fair_fulltext_source":"epmc_xml","fair_has_llm":true,"fair_computed_at":"2026-07-20T13:58:29.079869Z","clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}