{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T18:56:51Z","timestamp":1783105011844,"version":"3.54.6"},"reference-count":24,"publisher":"Oxford University Press (OUP)","issue":"4","license":[{"start":{"date-parts":[[2024,4,10]],"date-time":"2024-04-10T00:00:00Z","timestamp":1712707200000},"content-version":"vor","delay-in-days":12,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Start-up Funds"},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000060","name":"National Institute of Allergy and Infectious Diseases","doi-asserted-by":"publisher","award":["AI147084"],"award-info":[{"award-number":["AI147084"]}],"id":[{"id":"10.13039\/100000060","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000060","name":"National Institute of Allergy and Infectious Diseases","doi-asserted-by":"publisher","award":["AI159710"],"award-info":[{"award-number":["AI159710"]}],"id":[{"id":"10.13039\/100000060","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Solve ME\/CFS Initiative Ramsay Research Grant Program, Open Medicine Foundation"},{"name":"Department of Defense Lung Cancer Research Program","award":["LC190467"],"award-info":[{"award-number":["LC190467"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,3,29]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Motivation<\/jats:title>\n                  <jats:p>Discovering disease causative pathogens, particularly viruses without reference genomes, poses a technical challenge as they are often unidentifiable through sequence alignment. Machine learning prediction of patient high-throughput sequences unmappable to human and pathogen genomes may reveal sequences originating from uncharacterized viruses. Currently, there is a lack of software specifically designed for accurately predicting such viral sequences in human data.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>We developed a fast XGBoost method and software VirusPredictor leveraging an in-house viral genome database. Our two-step XGBoost models first classify each query sequence into one of three groups: infectious virus, endogenous retrovirus (ERV) or non-ERV human. The prediction accuracies increased as the sequences became longer, i.e. 0.76, 0.93, and 0.98 for 150\u2013350 (Illumina short reads), 850\u2013950 (Sanger sequencing data), and 2000\u20135000\u2009bp sequences, respectively. Then, sequences predicted to be from infectious viruses are further classified into one of six virus taxonomic subgroups, and the accuracies increased from 0.92 to &amp;gt;0.98 when query sequences increased from 150\u2013350 to &amp;gt;850\u2009bp. The results suggest that Illumina short reads should be de novo assembled into contigs (e.g. \u223c1000\u2009bp or longer) before prediction whenever possible. We applied VirusPredictor to multiple real genomic and metagenomic datasets and obtained high accuracies. VirusPredictor, a user-friendly open-source Python software, is useful for predicting the origins of patients\u2019 unmappable sequences. This study is the first to classify ERVs in infectious viral sequence prediction. This is also the first study combining virus sub-group predictions.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>www.dllab.org\/software\/VirusPredictor.html.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btae192","type":"journal-article","created":{"date-parts":[[2024,4,10]],"date-time":"2024-04-10T14:35:37Z","timestamp":1712759737000},"source":"Crossref","is-referenced-by-count":16,"title":["VirusPredictor: XGBoost-based software to predict virus-related sequences in human data"],"prefix":"10.1093","volume":"40","author":[{"given":"Guangchen","family":"Liu","sequence":"first","affiliation":[{"name":"Department of Microbiology and Molecular Genetics, University of Vermont , Burlington, Vermont 05405, United States"},{"name":"School of Mathematics, Shandong University , Jinan, Shandong 250100, China"},{"name":"School of Mathematics and Statistics, Ludong University , Yantai, Shandong 264025, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0327-1888","authenticated-orcid":false,"given":"Xun","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Microbiology and Molecular Genetics, University of Vermont , Burlington, Vermont 05405, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yihui","family":"Luan","sequence":"additional","affiliation":[{"name":"School of Mathematics, Shandong University , Jinan, Shandong 250100, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9214-4487","authenticated-orcid":false,"given":"Dawei","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Microbiology and Molecular Genetics, University of Vermont , Burlington, Vermont 05405, United States"},{"name":"Department of Immunology and Molecular Microbiology, Texas Tech University Health Sciences Center , Lubbock, Texas 79430, United States"},{"name":"ICanCME Research Network, Sainte-Justine University Hospital Research Center , Montreal, Quebec H3T 1C5, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2024,4,10]]},"reference":[{"key":"2024042700020419700_btae192-B1","doi-asserted-by":"crossref","first-page":"119641","DOI":"10.1016\/j.eswa.2023.119641","article-title":"Viral genome prediction from raw human DNA sequence samples by combining natural language processing and machine learning techniques","volume":"218","author":"Alshayeji","year":"2023","journal-title":"Expert Syst Appl"},{"key":"2024042700020419700_btae192-B2","doi-asserted-by":"crossref","first-page":"1396","DOI":"10.1093\/bioinformatics\/btv006","article-title":"Integrating alignment-based and alignment-free sequence similarity measures for biological sequence classification","volume":"31","author":"Borozan","year":"2015","journal-title":"Bioinformatics"},{"key":"2024042700020419700_btae192-B3","doi-asserted-by":"crossref","first-page":"4897","DOI":"10.1002\/jcb.26717","article-title":"Searching for human oncoviruses: histories, challenges, and opportunities","volume":"119","author":"Cao","year":"2018","journal-title":"J Cell Biochem"},{"key":"2024042700020419700_btae192-B4","first-page":"785","author":"Chen","year":"2016"},{"key":"2024042700020419700_btae192-B5","doi-asserted-by":"crossref","first-page":"819","DOI":"10.1101\/gr.242529.118","article-title":"A virome-wide clonal integration analysis platform for discovering cancer viral etiology","volume":"29","author":"Chen","year":"2019","journal-title":"Genome Res"},{"key":"2024042700020419700_btae192-B6","doi-asserted-by":"crossref","first-page":"1189","DOI":"10.1016\/j.ygeno.2020.12.004","article-title":"Sequencing facility and DNA source associated patterns of virus-mappable reads in whole-genome sequencing data","volume":"113","author":"Chen","year":"2021","journal-title":"Genomics"},{"key":"2024042700020419700_btae192-B7","doi-asserted-by":"crossref","first-page":"785","DOI":"10.1038\/s41467-023-36336-z","article-title":"A deep learning approach reveals unexplored landscape of viral expression in cancer","volume":"14","author":"Elbasir","year":"2023","journal-title":"Nat Commun"},{"key":"2024042700020419700_btae192-B8","doi-asserted-by":"crossref","first-page":"801113","DOI":"10.3389\/fcell.2021.801113","article-title":"Gene-based testing of interactions using XGBoost in genome-wide association studies","volume":"9","author":"Guo","year":"2021","journal-title":"Front Cell Dev Biol"},{"key":"2024042700020419700_btae192-B9","doi-asserted-by":"crossref","first-page":"9623","DOI":"10.1073\/pnas.1707009114","article-title":"Numerous uncharacterized and highly divergent microbes which colonize humans are revealed by circulating cell-free DNA","volume":"114","author":"Kowarsky","year":"2017","journal-title":"Proc Natl Acad Sci USA"},{"key":"2024042700020419700_btae192-B10","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/1687-6180-2012-50","article-title":"Novel methodologies for spectral classification of exon and intron sequences","volume":"2012","author":"Kwan","year":"2012","journal-title":"EURASIP J Adv Signal Process"},{"key":"2024042700020419700_btae192-B11","doi-asserted-by":"crossref","first-page":"1991","DOI":"10.1093\/bioinformatics\/btu177","article-title":"Fast alignment-free sequence comparison using spaced-word frequencies","volume":"30","author":"Leimeister","year":"2014","journal-title":"Bioinformatics"},{"key":"2024042700020419700_btae192-B12","doi-asserted-by":"crossref","first-page":"960","DOI":"10.1038\/s41564-021-00928-6","article-title":"Metagenomic compendium of 189,680 DNA viruses from the human gut microbiome","volume":"6","author":"Nayfach","year":"2021","journal-title":"Nat Microbiol"},{"key":"2024042700020419700_btae192-B13","doi-asserted-by":"crossref","first-page":"1725","DOI":"10.1101\/gr.194201","article-title":"SSAHA: a fast search method for large DNA databases","volume":"11","author":"Ning","year":"2001","journal-title":"Genome Res"},{"key":"2024042700020419700_btae192-B14","doi-asserted-by":"crossref","first-page":"4187","DOI":"10.3390\/s21124187","article-title":"Artificial breath classification using XGBoost algorithm for diabetes detection","volume":"21","author":"Paleczek","year":"2021","journal-title":"Sensors (Basel)"},{"key":"2024042700020419700_btae192-B15","author":"Rajkumar","year":"2022"},{"key":"2024042700020419700_btae192-B16","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1186\/s40168-017-0283-5","article-title":"VirFinder: a novel k-mer based tool for identifying viral sequences from assembled metagenomic data","volume":"5","author":"Ren","year":"2017","journal-title":"Microbiome"},{"key":"2024042700020419700_btae192-B17","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1007\/s40484-019-0187-4","article-title":"Identifying viruses from metagenomic data using deep learning","volume":"8","author":"Ren","year":"2020","journal-title":"Quant Biol"},{"key":"2024042700020419700_btae192-B18","doi-asserted-by":"crossref","first-page":"108197","DOI":"10.1016\/j.patcog.2021.108197","article-title":"A unified hierarchical XGBoost model for classifying priorities for COVID-19 vaccination campaign","volume":"121","author":"Romeo","year":"2022","journal-title":"Pattern Recognit"},{"key":"2024042700020419700_btae192-B19","doi-asserted-by":"crossref","first-page":"3074","DOI":"10.1093\/bioinformatics\/btr519","article-title":"Metavir: a web server dedicated to virome analysis","volume":"27","author":"Roux","year":"2011","journal-title":"Bioinformatics"},{"key":"2024042700020419700_btae192-B20","doi-asserted-by":"crossref","first-page":"427","DOI":"10.1016\/j.ipm.2009.03.002","article-title":"A systematic analysis of performance measures for classification tasks","volume":"45","author":"Sokolova","year":"2009","journal-title":"Inf Process Manag"},{"key":"2024042700020419700_btae192-B21","doi-asserted-by":"crossref","first-page":"343","DOI":"10.1093\/bib\/bbt067","article-title":"New developments of alignment-free sequence comparison: measures, statistics and next-generation sequencing","volume":"15","author":"Song","year":"2014","journal-title":"Brief Bioinform"},{"key":"2024042700020419700_btae192-B22","doi-asserted-by":"crossref","first-page":"e0222271","DOI":"10.1371\/journal.pone.0222271","article-title":"ViraMiner: deep learning on raw DNA sequences for identifying viral genomes in human samples","volume":"14","author":"Tampuu","year":"2019","journal-title":"PLoS One"},{"key":"2024042700020419700_btae192-B23","doi-asserted-by":"crossref","first-page":"513","DOI":"10.1093\/bioinformatics\/btg005","article-title":"Alignment-free sequence comparison-a review","volume":"19","author":"Vinga","year":"2003","journal-title":"Bioinformatics"},{"key":"2024042700020419700_btae192-B24","doi-asserted-by":"crossref","first-page":"eabf4130","DOI":"10.1126\/sciadv.abf4130","article-title":"Deep exploration of random Forest model boosts the interpretability of machine learning studies of complicated immune responses and lung burden of nanoparticles","volume":"7","author":"Yu","year":"2021","journal-title":"Sci Adv"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/advance-article-pdf\/doi\/10.1093\/bioinformatics\/btae192\/57206603\/btae192.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/40\/4\/btae192\/57341844\/btae192.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/40\/4\/btae192\/57341844\/btae192.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,4,27]],"date-time":"2024-04-27T00:03:18Z","timestamp":1714176198000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/doi\/10.1093\/bioinformatics\/btae192\/7643508"}},"subtitle":[],"editor":[{"given":"Pier Luigi","family":"Martelli","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"editor"}]}],"short-title":[],"issued":{"date-parts":[[2024,3,29]]},"references-count":24,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2024,3,29]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btae192","relation":{},"ISSN":["1367-4811"],"issn-type":[{"value":"1367-4811","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2024,4,1]]},"published":{"date-parts":[[2024,3,29]]},"article-number":"btae192"}}