Interactive microbial distribution analysis using BioAtlas.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:28460071", "kind": "science-record", "revision": 5, "content_hash": "sha256:b09693f5c7c80a665c86ce657fe26c6a4d60db85fc1e0e2dbc804cbc5eee14bc", "created_at": "2026-11-01T15:40:25Z", "updated_at": "2026-11-01T18:48:42Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Interactive microbial distribution analysis using BioAtlas.", "doi": "10.1093/nar/gkx304", "pmid": "28460071", "authors": ["Jesper Beltoft Lund", "Markus List", "Jan Baumbach"], "journal": "Nucleic acids research", "year": 2017, "abstract": "Massive amounts of 16S rRNA sequencing data have been stored in publicly accessible databases, such as GOLD, SILVA, GreenGenes (GG), and the Ribosomal Database Project (RDP). Many of these sequences are tagged with geo-locations. Nevertheless, researchers currently lack a user-friendly tool to analyze microbial distribution in a location-specific context. BioAtlas is an interactive web application that closes this gap between sequence databases, taxonomy profiling and geo/body-location information. It enables users to browse taxonomically annotated sequences across (i) the world map, (ii) human body maps and (iii) user-defined maps. It further allows for (iv) uploading of own sample data, which can be placed on existing maps to (v) browse the distribution of the associated taxonomies. Finally, BioAtlas enables users to (vi) contribute custom maps (e.g. for plants or animals) and to map taxonomies to pre-defined map locations. In summary, BioAtlas facilitates map-supported browsing of public 16S rRNA sequence data and analyses of user-provided sequences without requiring manual mapping to taxonomies and existing databases.\nAVAILABILITY: http://bioatlas.compbio.sdu.dk/.", "claims": [{"id": "claim-data-access", "statement": "We used SILVA SSU Ref NR 99, a non-redundant version of the high quality control database storing 645 151 sequences.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:28460071", "locator": "sections[5] \"DATA PROCESSING\" paragraph 2", "quote": "We used SILVA SSU Ref NR 99, a non-redundant version of the high quality control database storing 645 151 sequences."}], "state": "complete"}, {"id": "claim-target-result", "statement": "BioAtlas classified IMG/GOLD-derived 16S rRNA sequences with the Mothur classifier using the SILVA SSU Ref NR 99 reference database, successfully classifying 423,543 sequences (92.2%).", "kind": "quantitative", "target": {"value": 92.2, "unit": "per cent", "tolerance": null, "source": "Mothur was able to classify 423 543 sequences (92.2%)."}, "evidence": [{"asset": "source:pmid:28460071", "locator": "sections[5] \"DATA PROCESSING\" paragraph 2", "quote": "We used SILVA SSU Ref NR 99, a non-redundant version of the high quality control database storing 645 151 sequences."}, {"asset": "source:pmid:28460071", "locator": "sections[6] \"GOLD and IMG data of global microbiome diversity\" paragraph 2", "quote": "Of these, we extracted a total of 459 304 16S rRNA sequences for taxonomical classification in Mothur."}, {"asset": "source:pmid:28460071", "locator": "sections[6] \"GOLD and IMG data of global microbiome diversity\" paragraph 3", "quote": "Mothur was able to classify 423 543 sequences (92.2%)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": "BioAtlas classified IMG/GOLD-derived 16S rRNA sequences with the Mothur classifier using the SILVA SSU Ref NR 99 reference database, successfully classifying 423,543 sequences (92.2%).", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:28460071"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "blocked", "blocked_on": "data:accession_absent", "description": "The GEO series accession resolves and its sample accessions are listed. 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