{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,18]],"date-time":"2026-01-18T21:44:03Z","timestamp":1768772643697,"version":"3.49.0"},"reference-count":5,"publisher":"Oxford University Press (OUP)","issue":"6","license":[{"start":{"date-parts":[[2016,10,2]],"date-time":"2016-10-02T00:00:00Z","timestamp":1475366400000},"content-version":"vor","delay-in-days":3188,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/2.0\/uk\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2008,3,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Summary: It is important to preprocess high-throughput data generated from mass spectrometry experiments in order to obtain a successful proteomics analysis. Outlier detection is an important preprocessing step. A naive outlier detection approach may miss many true outliers and instead select many non-outliers because of the heterogeneity of the variability observed commonly in high-throughput data. Because of this issue, we developed a outlier detection software program accounting for the heterogeneous variability by utilizing linear, non-linear and non-parametric quantile regression techniques. Our program was developed using the R computer language. As a consequence, it can be used interactively and conveniently in the R environment.<\/jats:p>\n               <jats:p>Availability: An R package, OutlierD, is available at the Bioconductor project at http:\/\/www.bioconductor.org<\/jats:p>\n               <jats:p>Contact: \u00a0jael@korea.ac.kr<\/jats:p>\n               <jats:p>Supplementary information: Supplementary Data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btn012","type":"journal-article","created":{"date-parts":[[2008,1,11]],"date-time":"2008-01-11T01:13:48Z","timestamp":1200014028000},"page":"882-884","source":"Crossref","is-referenced-by-count":28,"title":["OutlierD: an R package for outlier detection using quantile regression on mass spectrometry data"],"prefix":"10.1093","volume":"24","author":[{"given":"HyungJun","family":"Cho","sequence":"first","affiliation":[{"name":"1 Department of Statistics, 2Department of Biostatistics, 3Institute of Statistics and 4Department of Chemistry, Korea University, Seoul, Korea"},{"name":"1 Department of Statistics, 2Department of Biostatistics, 3Institute of Statistics and 4Department of Chemistry, Korea University, Seoul, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yang-jin","family":"Kim","sequence":"additional","affiliation":[{"name":"1 Department of Statistics, 2Department of Biostatistics, 3Institute of Statistics and 4Department of Chemistry, Korea University, Seoul, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hee Jung","family":"Jung","sequence":"additional","affiliation":[{"name":"1 Department of Statistics, 2Department of Biostatistics, 3Institute of Statistics and 4Department of Chemistry, Korea University, Seoul, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sang-Won","family":"Lee","sequence":"additional","affiliation":[{"name":"1 Department of Statistics, 2Department of Biostatistics, 3Institute of Statistics and 4Department of Chemistry, Korea University, Seoul, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jae Won","family":"Lee","sequence":"additional","affiliation":[{"name":"1 Department of Statistics, 2Department of Biostatistics, 3Institute of Statistics and 4Department of Chemistry, Korea University, Seoul, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2008,1,10]]},"reference":[{"key":"2023020209512934800_B1","doi-asserted-by":"crossref","first-page":"33","DOI":"10.2307\/1913643","article-title":"Regression quantiles","volume":"46","author":"Koenker","year":"1978","journal-title":"Econometrics"},{"key":"2023020209512934800_B2","doi-asserted-by":"crossref","DOI":"10.1017\/CBO9780511754098","volume-title":"Quantile Regression.","author":"Koenker","year":"2005"},{"key":"2023020209512934800_B3","doi-asserted-by":"crossref","first-page":"1012","DOI":"10.1002\/elps.200600501","article-title":"Ultrahigh-pressure dual online solid phase extraction\/capillary reverse-phase liquid chromatography\/tandem mass spectrometry (DO-SPE\/cRPLC\/MS\/MS): a versatile separation platform for high-throughput and highly sensitive proteomic analyses","volume":"28","author":"Min","year":"2007","journal-title":"Electrophoresis"},{"key":"2023020209512934800_B4","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1021\/pr025556v","article-title":"Evaluation of multidimensional chromatography coupled with tandem mass spectrometry (LC\/LC-MS\/MS) for large-scale protein analysis: the yeast proteome","volume":"2","author":"Peng","year":"2003","journal-title":"J. Proteome Res"},{"key":"2023020209512934800_B5","doi-asserted-by":"crossref","first-page":"660","DOI":"10.1038\/nbt827","article-title":"Identification and quantification of N-linked glycoproteins using hydrazide chemistry, stable isotope labeling and mass spectrometry","volume":"21","author":"Zhang","year":"2003","journal-title":"Nat. Biotechnol"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/24\/6\/882\/49046930\/bioinformatics_24_6_882.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/24\/6\/882\/49046930\/bioinformatics_24_6_882.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,2,2]],"date-time":"2023-02-02T10:46:47Z","timestamp":1675334807000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/24\/6\/882\/193190"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2008,1,10]]},"references-count":5,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2008,3,15]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btn012","relation":{},"ISSN":["1367-4811","1367-4803"],"issn-type":[{"value":"1367-4811","type":"electronic"},{"value":"1367-4803","type":"print"}],"subject":[],"published-other":{"date-parts":[[2008,3,15]]},"published":{"date-parts":[[2008,1,10]]}}}