{"doi":"10.1186/s13059-024-03233-7","title":"Scoary2: rapid association of phenotypic multi-omics data with microbial pan-genomes","abstract":"<jats:title>Abstract</jats:title>\n                  <jats:p>\n                    Unraveling bacterial gene function drives progress in various areas, such as food production, pharmacology, and ecology. While omics technologies capture high-dimensional phenotypic data, linking them to genomic data is challenging, leaving 40–60% of bacterial genes undescribed. To address this bottleneck, we introduce\n                    <jats:italic>Scoary2</jats:italic>\n                    , an ultra-fast microbial genome-wide association studies (mGWAS) software. With its data exploration app and improved performance,\n                    <jats:italic>Scoary2</jats:italic>\n                    is the first tool to enable the study of large phenotypic datasets using mGWAS. As proof of concept, we explore the metabolome of yogurts, each produced with a different\n                    <jats:italic>Propionibacterium reichii</jats:italic>\n                    strain and discover two genes affecting carnitine metabolism.\n                  </jats:p>","journal":"Genome Biology","year":2024,"id":612244,"datarank":0.7931736154323021,"base_score":3.6635616461296463,"endowment":3.6635616461296463,"self_citation_contribution":0.5495342469194471,"citation_network_contribution":0.24363936851285511,"self_endowment_contribution":0.5495342469194471,"citer_contribution":0.24363936851285511,"corpus_percentile":null,"corpus_rank":null,"citation_count":38,"citer_count":35,"citers_with_citation_signal":15,"citers_with_endowment":15,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1576270,"name":"Grégory Pimentel","orcid":null,"position":1,"is_corresponding":false},{"id":1576271,"name":"Pascal Fuchsmann","orcid":null,"position":2,"is_corresponding":false},{"id":1576272,"name":"Mireille Tena Stern","orcid":null,"position":3,"is_corresponding":false},{"id":1576273,"name":"Ueli von Ah","orcid":null,"position":4,"is_corresponding":false},{"id":1576274,"name":"Guy Vergères","orcid":"0000-0003-4574-0590","position":5,"is_corresponding":false},{"id":1576275,"name":"Stephan Peischl","orcid":null,"position":6,"is_corresponding":false},{"id":577132,"name":"Ola Brynildsrud","orcid":"0000-0001-7566-4133","position":7,"is_corresponding":false},{"id":672929,"name":"Rémy Bruggmann","orcid":"0000-0001-5629-6363","position":8,"is_corresponding":false},{"id":1576276,"name":"Cornelia Bär","orcid":null,"position":9,"is_corresponding":false},{"id":1576269,"name":"Thomas Roder","orcid":null,"position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Scoary2: rapid association of phenotypic multi-omics data with microbial pan-genomes","abstract":"<jats:title>Abstract</jats:title>\n                  <jats:p>\n                    Unraveling bacterial gene function drives progress in various areas, such as food production, pharmacology, and ecology. While omics technologies capture high-dimensional phenotypic data, linking them to genomic data is challenging, leaving 40–60% of bacterial genes undescribed. To address this bottleneck, we introduce\n                    <jats:italic>Scoary2</jats:italic>\n                    , an ultra-fast microbial genome-wide association studies (mGWAS) software. With its data exploration app and improved performance,\n                    <jats:italic>Scoary2</jats:italic>\n                    is the first tool to enable the study of large phenotypic datasets using mGWAS. As proof of concept, we explore the metabolome of yogurts, each produced with a different\n                    <jats:italic>Propionibacterium reichii</jats:italic>\n                    strain and discover two genes affecting carnitine metabolism.\n                  </jats:p>","is_dataset_classified":null,"base_score":3.6375861597263857,"endowment":3.6375861597263857,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"38605417","pmcid":"PMC11007987","openalex_id":"https://openalex.org/W4394717964","authors":[],"funders":[{"funder_name":"Gebert Rüf Stiftung","grant_id":"GRS-070/17","title":null},{"funder_name":"Kanton Bern","grant_id":"","title":null}],"total_grants":2,"fwci":5.9852,"citation_percentile":0.97444847,"influential_citations":0,"citation_trend":[{"year":2024,"count":1},{"year":2025,"count":16},{"year":2026,"count":20}],"oa_status":"gold","license":"cc-by","oa_locations":[{"url":"https://genomebiology.biomedcentral.com/counter/pdf/10.1186/s13059-024-03233-7","host_type":"journal"},{"url":"https://genomebiology.biomedcentral.com/counter/pdf/10.1186/s13059-024-03233-7","host_type":"publisher"},{"url":"https://link.springer.com/content/pdf/10.1186/s13059-024-03233-7.pdf","host_type":"publisher"},{"url":"https://link.springer.com/article/10.1186/s13059-024-03233-7/fulltext.html","host_type":"publisher"},{"url":"https://doi.org/10.1186/s13059-024-03233-7","host_type":"journal"},{"url":"https://pubmed.ncbi.nlm.nih.gov/38605417","host_type":"repository"},{"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11007987","host_type":"repository"},{"url":"https://boris.unibe.ch/195911/","host_type":"repository"},{"url":"https://doaj.org/article/e5fbdc092e484817948c29a2bc086fcd","host_type":"repository"},{"url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11007987/pdf/13059_2024_Article_3233.pdf","host_type":"repository"},{"url":"https://europepmc.org/articles/PMC11007987","host_type":"Europe_PMC"},{"url":"https://europepmc.org/articles/PMC11007987?pdf=render","host_type":"Europe_PMC"}],"fields_of_study":["Metabolomics and Mass Spectrometry Studies","Genomics and Phylogenetic Studies","Gut microbiota and health"],"mesh_terms":["Multiomics","Genes, Bacterial","Phenotype","Genomics","Genome-Wide Association Study"],"keywords":["Biology","Metabolome","Genome","Computational biology","Phenotype","Omics","Bottleneck","Genomics","Gene","Genetics","Metabolomics","Bioinformatics","Computer science","Bacteria","Metabolite","Prokaryote","Gwas","Genotype-phenotype Association","Fermented Food","Pan-genome","Microbial Genome-wide Association Studies","Bgwa"],"sdg_mappings":[{"sdg_number":0,"sdg_label":"Zero hunger"}],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-02T02:24:49.039971Z","pmid":null,"pmcid":null,"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":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}