OutlierD: an R package for outlier detection using quantile regression on mass spectrometry data
DC Field | Value | Language |
---|---|---|
dc.contributor.author | HyungJun Cho | - |
dc.contributor.author | Yang-jin Kim | - |
dc.contributor.author | Hee Jung Jung | - |
dc.contributor.author | Sang-Won Lee | - |
dc.contributor.author | Jae Won Lee | - |
dc.date.accessioned | 2022-04-19T11:05:07Z | - |
dc.date.available | 2022-04-19T11:05:07Z | - |
dc.date.issued | 2008-01 | - |
dc.identifier.issn | 1367-4803 | - |
dc.identifier.issn | 1367-4811 | - |
dc.identifier.uri | https://scholarworks.sookmyung.ac.kr/handle/2020.sw.sookmyung/148248 | - |
dc.description.abstract | 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. | - |
dc.format.extent | 3 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | OXFORD UNIV PRESS | - |
dc.title | OutlierD: an R package for outlier detection using quantile regression on mass spectrometry data | - |
dc.type | Article | - |
dc.publisher.location | 미국 | - |
dc.identifier.doi | 10.1093/bioinformatics/btn012 | - |
dc.identifier.scopusid | 2-s2.0-40749141227 | - |
dc.identifier.wosid | 000254010400027 | - |
dc.identifier.bibliographicCitation | BIOINFORMATICS, v.24, no.6, pp 882 - 884 | - |
dc.citation.title | BIOINFORMATICS | - |
dc.citation.volume | 24 | - |
dc.citation.number | 6 | - |
dc.citation.startPage | 882 | - |
dc.citation.endPage | 884 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.identifier.url | https://scienceon.kisti.re.kr/srch/selectPORSrchArticle.do?cn=NART44034655&SITE=CLICK | - |
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