{"doi":"10.1101/2025.09.07.674724","title":"Identification of Sample Processing Errors in Microbiome Studies Using Host Genetic Profiles","abstract":"<jats:title>Abstract</jats:title>\n                <jats:p>In microbiome studies, sample processing errors are frequent and difficult to detect, especially in large studies involving multiple sites, personnel, and sample types. We present two complementary approaches to identify such errors using host DNA profiled via metagenomic sequencing of microbiome samples. The first approach compares host SNPs inferred from metagenomics to independently obtained genotypes (e.g., microarray genotypes) to match samples to their donors, while the second method compares metagenomics-inferred SNPs between samples to identify samples supplied by the same donor. Furthermore, we demonstrate that combining these methods with experimental metadata provides greater confidence in the identification of errors. Analyzing a longitudinal vaginal microbiome dataset, we demonstrate the ability of our approach to identify mislabeled samples. Using subsampling, we further show that our methods are robust to low sequencing coverage. Overall, our analysis highlights the frequency of processing errors in microbiome studies. We therefore recommend applying error-detection methods in all studies with suitable data.</jats:p>","journal":null,"year":null,"id":676745,"datarank":0.10397207708399181,"base_score":0.6931471805599453,"endowment":0.6931471805599453,"self_citation_contribution":0.10397207708399181,"citation_network_contribution":0.0,"self_endowment_contribution":0.10397207708399181,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":1,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"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":1402213,"name":"Aya Brown Kav","orcid":"0000-0003-2085-126X","position":1,"is_corresponding":false},{"id":1022445,"name":"William F. Kindschuh","orcid":"0000-0002-7433-7808","position":2,"is_corresponding":false},{"id":715278,"name":"Heekuk Park","orcid":"0000-0001-5815-9717","position":3,"is_corresponding":false},{"id":563835,"name":"Raiyan R. Khan","orcid":null,"position":4,"is_corresponding":false},{"id":1768202,"name":"Emily Watters","orcid":"0009-0006-8817-7362","position":5,"is_corresponding":false},{"id":305312,"name":"Itsik Pe’er","orcid":"0000-0002-6128-7231","position":6,"is_corresponding":false},{"id":246804,"name":"Anne‐Catrin Uhlemann","orcid":"0000-0002-9798-4768","position":7,"is_corresponding":false},{"id":237264,"name":"Tal Korem","orcid":"0000-0002-0609-0858","position":8,"is_corresponding":false},{"id":1026637,"name":"J Urban","orcid":"0000-0002-6950-6435","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Identification of Sample Processing Errors in Microbiome Studies Using Host Genetic Profiles","abstract":"<jats:title>Abstract</jats:title>\n                <jats:p>In microbiome studies, sample processing errors are frequent and difficult to detect, especially in large studies involving multiple sites, personnel, and sample types. We present two complementary approaches to identify such errors using host DNA profiled via metagenomic sequencing of microbiome samples. The first approach compares host SNPs inferred from metagenomics to independently obtained genotypes (e.g., microarray genotypes) to match samples to their donors, while the second method compares metagenomics-inferred SNPs between samples to identify samples supplied by the same donor. Furthermore, we demonstrate that combining these methods with experimental metadata provides greater confidence in the identification of errors. Analyzing a longitudinal vaginal microbiome dataset, we demonstrate the ability of our approach to identify mislabeled samples. Using subsampling, we further show that our methods are robust to low sequencing coverage. Overall, our analysis highlights the frequency of processing errors in microbiome studies. We therefore recommend applying error-detection methods in all studies with suitable data.</jats:p>","is_dataset_classified":null,"base_score":0.6931471805599453,"endowment":0.6931471805599453,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"40964394","pmcid":null,"openalex_id":"https://openalex.org/W4414152079","authors":[],"funders":[{"funder_name":"Eunice Kennedy Shriver National Institute of Child Health and Human Development","grant_id":"R01 HD106017","title":null},{"funder_name":"Eunice Kennedy Shriver National Institute of Child Health and Human Development","grant_id":"R01 HD114715","title":null},{"funder_name":"Eunice Kennedy Shriver National Institute of Child Health and Human Development","grant_id":"5F30 HD108886","title":null},{"funder_name":"Eunice Kennedy Shriver National Institute of Child Health and Human Development","grant_id":"F31 HD115394","title":null},{"funder_name":"Eunice Kennedy Shriver National Institute of Child Health and Human Development","grant_id":"U10 HD063036","title":null},{"funder_name":"Eunice Kennedy Shriver National Institute of Child Health and Human Development","grant_id":"U10 HD063072","title":null},{"funder_name":"Eunice Kennedy Shriver National Institute of Child Health and Human Development","grant_id":"U10 HD063047","title":null},{"funder_name":"Eunice Kennedy Shriver National Institute of Child Health and Human Development","grant_id":"U10 HD063037","title":null},{"funder_name":"Eunice Kennedy Shriver National Institute of Child Health and Human Development","grant_id":"U10 HD063041","title":null},{"funder_name":"Eunice Kennedy Shriver National Institute of Child Health and Human Development","grant_id":"U10 HD063020","title":null},{"funder_name":"Eunice Kennedy Shriver National Institute of Child Health and Human Development","grant_id":"U10 HD063046","title":null},{"funder_name":"Eunice Kennedy Shriver National Institute of Child Health and Human Development","grant_id":"U10 HD063048","title":null},{"funder_name":"Eunice Kennedy Shriver National Institute of Child Health and Human Development","grant_id":"U10 HD063053","title":null},{"funder_name":"United States National Library of Medicine","grant_id":"T15 LM007079","title":null},{"funder_name":"Clinical and Translational Science Institute","grant_id":"UL1 TR001108","title":null},{"funder_name":"Clinical and Translational Science Institute","grant_id":"UL1 TR000153","title":null},{"funder_name":"NICHD NIH HHS","grant_id":"F30 HD108886","title":null}],"total_grants":17,"fwci":null,"citation_percentile":null,"influential_citations":0,"citation_trend":[{"year":2025,"count":1}],"oa_status":"green","license":"cc-by","oa_locations":[{"url":"https://www.biorxiv.org/content/biorxiv/early/2025/09/12/2025.09.07.674724.full.pdf","host_type":"repository"},{"url":"https://www.biorxiv.org/content/biorxiv/early/2025/09/12/2025.09.07.674724.full.pdf","host_type":"repository"},{"url":"https://syndication.highwire.org/content/doi/10.1101/2025.09.07.674724","host_type":"publisher"},{"url":"https://doi.org/10.1101/2025.09.07.674724","host_type":"repository"},{"url":"https://pubmed.ncbi.nlm.nih.gov/40964394","host_type":"repository"},{"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/12440029","host_type":"repository"},{"url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC12440029/","host_type":"repository"}],"fields_of_study":["Gut microbiota and health","Cancer Genomics and Diagnostics","Molecular Biology Techniques and Applications"],"mesh_terms":[],"keywords":["Microbiome","Metagenomics","Identification (biology)","Sample (material)","Host (biology)","Replicate","Single-nucleotide polymorphism","DNA sequencing"],"sdg_mappings":[],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-17T03:01:57.020047Z","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":[]}