SPARTA: super-fast permutation approach to approximate extremely low p-values
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Leem, Sangseob | - |
dc.contributor.author | Lee, Dae Ho | - |
dc.contributor.author | Park, Taesung | - |
dc.date.available | 2020-02-27T16:41:05Z | - |
dc.date.created | 2020-02-06 | - |
dc.date.issued | 2018-01 | - |
dc.identifier.issn | 1748-5673 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/5347 | - |
dc.description.abstract | The permutation test, a non-parametric method for assessing statistical significance, now widely used in many disciplines, including bioinformatics, is very useful in situations where a null distribution, of test statistics, is unknown or hard to determine. In permutation tests, the precision of significance depends on the number of permutations, although computation time precludes achieving extremely low p-values. In this paper, we propose a novel strategy, for approximating extremely low p-values. Our proposed method consists of three steps: (1) divide data into subsets and perform permutation tests for the subsets; (2) integrate p-values by Stouffer's z-score method; and (3) repeat the first and second steps, and average them. We herein demonstrate and validate our method, using simulation studies and two real biological examples. Those assessments showed that two p-values of about 1.0e-20 and 1.0e-50 could be well-estimated by the proposed method, in a single day, for samples larger than 5000. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | INDERSCIENCE ENTERPRISES LTD | - |
dc.relation.isPartOf | INTERNATIONAL JOURNAL OF DATA MINING AND BIOINFORMATICS | - |
dc.title | SPARTA: super-fast permutation approach to approximate extremely low p-values | - |
dc.type | Article | - |
dc.type.rims | ART | - |
dc.description.journalClass | 1 | - |
dc.identifier.wosid | 000464168300005 | - |
dc.identifier.bibliographicCitation | INTERNATIONAL JOURNAL OF DATA MINING AND BIOINFORMATICS, v.21, no.4, pp.352 - 364 | - |
dc.identifier.scopusid | 2-s2.0-85064278789 | - |
dc.citation.endPage | 364 | - |
dc.citation.startPage | 352 | - |
dc.citation.title | INTERNATIONAL JOURNAL OF DATA MINING AND BIOINFORMATICS | - |
dc.citation.volume | 21 | - |
dc.citation.number | 4 | - |
dc.contributor.affiliatedAuthor | Lee, Dae Ho | - |
dc.type.docType | Article | - |
dc.subject.keywordAuthor | permutation test | - |
dc.subject.keywordAuthor | low p-value | - |
dc.subject.keywordAuthor | rapid approximation | - |
dc.subject.keywordPlus | DIFFERENTIAL ABUNDANCE ANALYSIS | - |
dc.subject.keywordPlus | WIDE ASSOCIATION | - |
dc.subject.keywordPlus | ALGORITHM | - |
dc.relation.journalResearchArea | Mathematical & Computational Biology | - |
dc.relation.journalWebOfScienceCategory | Mathematical & Computational Biology | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
1342, Seongnam-daero, Sujeong-gu, Seongnam-si, Gyeonggi-do, Republic of Korea(13120)031-750-5114
COPYRIGHT 2020 Gachon University All Rights Reserved.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.