{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,14]],"date-time":"2026-02-14T10:17:53Z","timestamp":1771064273472,"version":"3.50.1"},"reference-count":24,"publisher":"Oxford University Press (OUP)","issue":"23","license":[{"start":{"date-parts":[[2021,7,13]],"date-time":"2021-07-13T00:00:00Z","timestamp":1626134400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"name":"European Union\u2019s Horizon 2020 Research and Innovation Program","award":["847912"],"award-info":[{"award-number":["847912"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,12,7]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Motivation<\/jats:title>\n                  <jats:p>Log-rank test is a widely used test that serves to assess the statistical significance of observed differences in survival, when comparing two or more groups. The log-rank test is based on several assumptions that support the validity of the calculations. It is naturally assumed, implicitly, that no errors occur in the labeling of the samples. That is, the mapping between samples and groups is perfectly correct. In this work, we investigate how test results may be affected when considering some errors in the original labeling.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>We introduce and define the uncertainty that arises from labeling errors in log-rank test. In order to deal with this uncertainty, we develop a novel algorithm for efficiently calculating a stability interval around the original log-rank P-value and prove its correctness. We demonstrate our algorithm on several datasets.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>We provide a Python implementation, called LoRSI, for calculating the stability interval using our algorithm https:\/\/github.com\/YakhiniGroup\/LoRSI.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Supplementary information<\/jats:title>\n                  <jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btab495","type":"journal-article","created":{"date-parts":[[2021,7,2]],"date-time":"2021-07-02T20:18:00Z","timestamp":1625257080000},"page":"4451-4459","source":"Crossref","is-referenced-by-count":4,"title":["On the stability of log-rank test under labeling errors"],"prefix":"10.1093","volume":"37","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3067-667X","authenticated-orcid":false,"given":"Ben","family":"Galili","sequence":"first","affiliation":[{"name":"Faculty of Computer Science, Technion-Israel Institute of Technology , Haifa, Israel"}]},{"given":"Anat","family":"Samohi","sequence":"additional","affiliation":[{"name":"Arazi School of Computer Science, Interdisciplinary Center , Herzliya, Israel"}]},{"given":"Zohar","family":"Yakhini","sequence":"additional","affiliation":[{"name":"Faculty of Computer Science, Technion-Israel Institute of Technology , Haifa, Israel"},{"name":"Arazi School of Computer Science, Interdisciplinary Center , Herzliya, Israel"}]}],"member":"286","published-online":{"date-parts":[[2021,7,13]]},"reference":[{"key":"2023061310491908800_btab495-B1","doi-asserted-by":"crossref","first-page":"1235","DOI":"10.12688\/f1000research.15789.1","article-title":"TRGAted: a web tool for survival analysis using protein data in the cancer genome atlas","volume":"7","author":"Borcherding","year":"2018","journal-title":"F1000Res"},{"key":"2023061310491908800_btab495-B2","volume-title":"Elements of Information Theory","author":"Cover","year":"1999"},{"key":"2023061310491908800_btab495-B3","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1186\/2043-9113-1-37","article-title":"Characterization of uncertainty in the classification of multivariate assays: application to pam50 centroid-based genomic predictors for breast cancer treatment plans","volume":"1","author":"Ebbert","year":"2011","journal-title":"J. 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