{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,22]],"date-time":"2026-01-22T23:22:05Z","timestamp":1769124125776,"version":"3.49.0"},"reference-count":17,"publisher":"Oxford University Press (OUP)","issue":"14","license":[{"start":{"date-parts":[[2022,5,27]],"date-time":"2022-05-27T00:00:00Z","timestamp":1653609600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R21ES032117"],"award-info":[{"award-number":["R21ES032117"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["P30ES019776"],"award-info":[{"award-number":["P30ES019776"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["1R01GM124061"],"award-info":[{"award-number":["1R01GM124061"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100020785","name":"Shenzhen Research Institute of Big Data","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100020785","id-type":"DOI","asserted-by":"publisher"}]},{"name":"University Development Fund of CUHK-Shenzhen"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,7,11]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Motivation<\/jats:title><jats:p>Testing for pathway enrichment is an important aspect in the analysis of untargeted metabolomics data. Due to the unique characteristics of untargeted metabolomics data, some key issues have not been fully addressed in existing pathway testing algorithms: (i) matching uncertainty between data features and metabolites; (ii) lacking of method to analyze positive mode and negative mode liquid chromatography\u2013mass spectrometry (LC\/MS) data simultaneously on the same set of subjects; (iii) the incompleteness of pathways in individual software packages.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>We developed an innovative R\/Bioconductor package: metabolic pathway testing with positive and negative mode data (metapone), which can perform two novel statistical tests that take matching uncertainty into consideration\u2014(i) a weighted gene set enrichment analysis-type test and (ii) a permutation-based weighted hypergeometric test. The package is capable of combining positive- and negative-ion mode results in a single testing scheme. For comprehensiveness, the built-in pathways were manually curated from three sources: Kyoto Encyclopedia of Genes and Genomes, Mummichog and The Small Molecule Pathway Database.<\/jats:p><\/jats:sec><jats:sec><jats:title>Availability and implementation<\/jats:title><jats:p>The package is available at https:\/\/bioconductor.org\/packages\/devel\/bioc\/html\/metapone.html.<\/jats:p><\/jats:sec><jats:sec><jats:title>Supplementary information<\/jats:title><jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p><\/jats:sec>","DOI":"10.1093\/bioinformatics\/btac364","type":"journal-article","created":{"date-parts":[[2022,5,31]],"date-time":"2022-05-31T19:57:49Z","timestamp":1654027069000},"page":"3662-3664","source":"Crossref","is-referenced-by-count":18,"title":["Metapone: a Bioconductor package for joint pathway testing for untargeted metabolomics data"],"prefix":"10.1093","volume":"38","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6080-4076","authenticated-orcid":false,"given":"Leqi","family":"Tian","sequence":"first","affiliation":[{"name":"Shenzhen Research Institute of Big Data , Shenzhen 518712, China"},{"name":"School of Data Science, The Chinese University of Hong Kong \u2013 Shenzhen , Shenzhen 518712, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhenjiang","family":"Li","sequence":"additional","affiliation":[{"name":"Gangarosa Department of Environmental Health, Emory University , Atlanta, GA 30322, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guoxuan","family":"Ma","sequence":"additional","affiliation":[{"name":"School of Data Science, The Chinese University of Hong Kong \u2013 Shenzhen , Shenzhen 518712, China"},{"name":"Department of Biostatistics, University of Michigan , Ann Arbor, MI 48109, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaoyue","family":"Zhang","sequence":"additional","affiliation":[{"name":"Gangarosa Department of Environmental Health, Emory University , Atlanta, GA 30322, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ziyin","family":"Tang","sequence":"additional","affiliation":[{"name":"Gangarosa Department of Environmental Health, Emory University , Atlanta, GA 30322, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Siheng","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Data Science, The Chinese University of Hong Kong \u2013 Shenzhen , Shenzhen 518712, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jian","family":"Kang","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, University of Michigan , Ann Arbor, MI 48109, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Donghai","family":"Liang","sequence":"additional","affiliation":[{"name":"Gangarosa Department of Environmental Health, Emory University , Atlanta, GA 30322, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tianwei","family":"Yu","sequence":"additional","affiliation":[{"name":"Shenzhen Research Institute of Big Data , Shenzhen 518712, China"},{"name":"School of Data Science, The Chinese University of Hong Kong \u2013 Shenzhen , Shenzhen 518712, China"},{"name":"Warshel Institute , Shenzhen, Guangdong 518712, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2022,5,27]]},"reference":[{"key":"2023041405364705100_","doi-asserted-by":"crossref","first-page":"1261","DOI":"10.1021\/acs.jproteome.6b00861","article-title":"Network marker selection for untargeted LC\u2013MS metabolomics data","volume":"16","author":"Cai","year":"2017","journal-title":"J. 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