{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,17]],"date-time":"2025-10-17T13:46:00Z","timestamp":1760708760461},"reference-count":10,"publisher":"Oxford University Press (OUP)","issue":"5","license":[{"start":{"date-parts":[[2016,10,2]],"date-time":"2016-10-02T00:00:00Z","timestamp":1475366400000},"content-version":"vor","delay-in-days":706,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2015,3,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Summary: MetMSLine represents a complete collection of functions in the R programming language as an accessible GUI for biomarker discovery in large-scale liquid-chromatography high-resolution mass spectral datasets from acquisition through to final metabolite identification forming a backend to output from any peak-picking software such as XCMS. MetMSLine automatically creates subdirectories, data tables and relevant figures at the following steps: (i) signal smoothing, normalization, filtration and noise transformation (PreProc.QC.LSC.R); (ii) PCA and automatic outlier removal (Auto.PCA.R); (iii) automatic regression, biomarker selection, hierarchical clustering and cluster ion\/artefact identification (Auto.MV.Regress.R); (iv) Biomarker\u2014MS\/MS fragmentation spectra matching and fragment\/neutral loss annotation (Auto.MS.MS.match.R) and (v) semi-targeted metabolite identification based on a list of theoretical masses obtained from public databases (DBAnnotate.R).<\/jats:p>\n               <jats:p>Availability and implementation: All source code and suggested parameters are available in an un-encapsulated layout on http:\/\/wmbedmands.github.io\/MetMSLine\/. Readme files and a synthetic dataset of both X-variables (simulated LC\u2013MS data), Y-variables (simulated continuous variables) and metabolite theoretical masses are also available on our GitHub repository.<\/jats:p>\n               <jats:p>Contact: \u00a0ScalbertA@iarc.fr<\/jats:p>","DOI":"10.1093\/bioinformatics\/btu705","type":"journal-article","created":{"date-parts":[[2014,10,28]],"date-time":"2014-10-28T04:40:37Z","timestamp":1414471237000},"page":"788-790","source":"Crossref","is-referenced-by-count":27,"title":["MetMSLine: an automated and fully integrated pipeline for rapid processing of high-resolution LC\u2013MS metabolomic datasets"],"prefix":"10.1093","volume":"31","author":[{"given":"William M. 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