{"doi":"10.1093/bib/bbac541","title":"Learning single-cell chromatin accessibility profiles using meta-analytic marker genes","abstract":"MOTIVATION: Single-cell assay for transposase accessible chromatin using sequencing (scATAC-seq) is a valuable resource to learn cis-regulatory elements such as cell-type specific enhancers and transcription factor binding sites. However, cell-type identification of scATAC-seq data is known to be challenging due to the heterogeneity derived from different protocols and the high dropout rate. RESULTS: In this study, we perform a systematic comparison of seven scATAC-seq datasets of mouse brain to benchmark the efficacy of neuronal cell-type annotation from gene sets. We find that redundant marker genes give a dramatic improvement for a sparse scATAC-seq annotation across the data collected from different studies. Interestingly, simple aggregation of such marker genes achieves performance comparable or higher than that of machine-learning classifiers, suggesting its potential for downstream applications. Based on our results, we reannotated all scATAC-seq data for detailed cell types using robust marker genes. Their meta scATAC-seq profiles are publicly available at https://gillisweb.cshl.edu/Meta_scATAC. Furthermore, we trained a deep neural network to predict chromatin accessibility from only DNA sequence and identified key motifs enriched for each neuronal subtype. Those predicted profiles are visualized together in our database as a valuable resource to explore cell-type specific epigenetic regulation in a sequence-dependent and -independent manner.","journal":"Briefings in Bioinformatics","year":2022,"id":287103,"datarank":0.3152127931346581,"base_score":1.6094379124341003,"endowment":1.6094379124341003,"self_citation_contribution":0.24141568686511508,"citation_network_contribution":0.073797106269543,"self_endowment_contribution":0.24141568686511508,"citer_contribution":0.073797106269543,"corpus_percentile":46.49957453392125,"corpus_rank":6917,"citation_count":4,"citer_count":4,"citers_with_citation_signal":3,"citers_with_endowment":3,"datacite_reuse_total":0,"is_dataset":true,"is_dataset_confidence":0.7657,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2022-01-01","fair_score":50.0,"fair_percentile":62.702537450321,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":820021,"name":"Ziqi Tang","orcid":"0000-0001-7585-915X","position":1,"is_corresponding":false},{"id":38337,"name":"Stephan Fischer","orcid":"0000-0002-7034-4103","position":2,"is_corresponding":false},{"id":820022,"name":"Chandana Rajesh","orcid":"0000-0002-0441-6527","position":3,"is_corresponding":false},{"id":820023,"name":"Rohit Tripathy","orcid":"0000-0003-0808-1194","position":4,"is_corresponding":false},{"id":298873,"name":"Peter K. Koo","orcid":"0000-0001-8722-0038","position":5,"is_corresponding":false},{"id":107897,"name":"Jesse Gillis","orcid":"0000-0002-0936-9774","position":6,"is_corresponding":false},{"id":266831,"name":"Risa Karakida Kawaguchi","orcid":"0000-0003-1764-5721","position":0,"is_corresponding":true}],"reference_count":50,"raw_metadata":null,"created_at":"2026-07-19T00:29:56.781756Z","pmid":"36549922","pmcid":"PMC9851328","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":50.0,"fair_a":81.25,"fair_i":0.0,"fair_r":33.3333,"fair_zscore":0.6155,"fair_rationale":{"fair_score":50.0,"has_llm":true,"taxonomy_version":"fair_taxonomy_v5","dimensions":{"F":{"name":"Findable","score":50.0,"criteria":[{"key":"f_dataset_pid","label":"Persistent identifier for the data","kind":"llm","weight":2.0,"fraction":0.5,"verdict":"partial","evidence":"https://gillisweb.cshl.edu/Meta_scATAC","grounded":true,"rationale":"The paper gives a web URL for the data, not a persistent identifier scheme (DOI, Handle, etc.).","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":"Meta scATAC-seq server","grounded":true,"rationale":"The data are hosted on a lab server (gillisweb.cshl.edu), which is not a curated repository from re3data/FAIRsharing.","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":"Source codes and marker gene sets are available at https://github.com/carushi/Catactor . 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'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 reuse license is stated for the data; the CC BY-NC license applies only to the article.","gain":16.67,"priority":"essential","scored":true},{"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 genomics / sequencing data, deposit in GEO (GSE accession), SRA (SRP/SRR) or ENA/BioProject (PRJEB/PRJNA).","anchors":["yes","partial","no"],"verdict":"partial","current":0.5,"evidence":"https://gillisweb.cshl.edu/Meta_scATAC","why":"The paper gives a web URL for the data, not a persistent identifier scheme (DOI, Handle, etc.).","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. 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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":"The corresponding GEO IDs of the collected studies are GSE100033, GSE111586, GSE123576, GSE127257, GSE126074 and GSE130399.","why":"The paper provides GEO accession numbers for the external datasets it used, which are identifiers of resources other than its own data. [downgraded to 'no' — no verifiable quote from the paper] [majority verdict 'no' (4/5 passes agreed)]","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. 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Prefer open genomics / sequencing formats such as FASTQ, BAM or VCF.","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."],"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":"2026-07-20T13:04:06.350420Z","clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}