{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,22]],"date-time":"2026-07-22T04:03:25Z","timestamp":1784693005148,"version":"3.55.0"},"reference-count":24,"publisher":"Oxford University Press (OUP)","issue":"15","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2009,8,1]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Motivation: Liquid chromatography-mass spectrometry (LC\/MS) profiling is a promising approach for the quantification of metabolites from complex biological samples. Significant challenges exist in the analysis of LC\/MS data, including noise reduction, feature identification\/ quantification, feature alignment and computation efficiency.<\/jats:p><jats:p>Result: Here we present a set of algorithms for the processing of high-resolution LC\/MS data. The major technical improvements include the adaptive tolerance level searching rather than hard cutoff or binning, the use of non-parametric methods to fine-tune intensity grouping, the use of run filter to better preserve weak signals and the model-based estimation of peak intensities for absolute quantification. The algorithms are implemented in an R package apLCMS, which can efficiently process large LC\/ MS datasets.<\/jats:p><jats:p>Availability: The R package apLCMS is available at www.sph.emory.edu\/apLCMS.<\/jats:p><jats:p>Contact: \u00a0tyu8@sph.emory.edu<\/jats:p><jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btp291","type":"journal-article","created":{"date-parts":[[2009,5,5]],"date-time":"2009-05-05T01:06:55Z","timestamp":1241485615000},"page":"1930-1936","source":"Crossref","is-referenced-by-count":382,"title":["apLCMS\u2014adaptive processing of high-resolution LC\/MS data"],"prefix":"10.1093","volume":"25","author":[{"given":"Tianwei","family":"Yu","sequence":"first","affiliation":[{"name":"1 Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta and 2 Department of Medicine, School of Medicine, Emory University, Atlanta, GA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Youngja","family":"Park","sequence":"additional","affiliation":[{"name":"1 Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta and 2 Department of Medicine, School of Medicine, Emory University, Atlanta, GA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jennifer M.","family":"Johnson","sequence":"additional","affiliation":[{"name":"1 Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta and 2 Department of Medicine, School of Medicine, Emory University, Atlanta, GA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dean P.","family":"Jones","sequence":"additional","affiliation":[{"name":"1 Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta and 2 Department of Medicine, School of Medicine, Emory University, Atlanta, GA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2009,5,4]]},"reference":[{"key":"2023013112045645300_B1","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1016\/j.chroma.2008.03.033","article-title":"Feature detection and alignment of hyphenated chromatographic-mass spectrometric data. 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