{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,4]],"date-time":"2026-03-04T13:49:11Z","timestamp":1772632151378,"version":"3.50.1"},"reference-count":8,"publisher":"Oxford University Press (OUP)","issue":"7","license":[{"start":{"date-parts":[[2016,10,2]],"date-time":"2016-10-02T00:00:00Z","timestamp":1475366400000},"content-version":"vor","delay-in-days":2797,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/2.0\/uk\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2009,4,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Summary: Qvality is a C++ program for estimating two types of standard statistical confidence measures: the q-value, which is an analog of the p-value that incorporates multiple testing correction, and the posterior error probability (PEP, also known as the local false discovery rate), which corresponds to the probability that a given observation is drawn from the null distribution. In computing q-values, qvality employs a standard bootstrap procedure to estimate the prior probability of a score being from the null distribution; for PEP estimation, qvality relies upon non-parametric logistic regression. Relative to other tools for estimating statistical confidence measures, qvality is unique in its ability to estimate both types of scores directly from a null distribution, without requiring the user to calculate p-values.<\/jats:p>\n               <jats:p>Availability: A web server, C++ source code and binaries are available under MIT license at http:\/\/noble.gs.washington.edu\/proj\/qvality<\/jats:p>\n               <jats:p>Contact: \u00a0lukas.kall@cbr.su.se<\/jats:p>\n               <jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btp021","type":"journal-article","created":{"date-parts":[[2009,2,5]],"date-time":"2009-02-05T01:56:04Z","timestamp":1233798964000},"page":"964-966","source":"Crossref","is-referenced-by-count":92,"title":["<scp>qvality<\/scp>: non-parametric estimation of <i>q<\/i>-values and posterior error probabilities"],"prefix":"10.1093","volume":"25","author":[{"given":"Lukas","family":"K\u00e4ll","sequence":"first","affiliation":[{"name":"1 Center for Biomembrane Research, Department of Biochemistry and Biophysics, Stockholm University, Sweden, 2Department of Genome Sciences, University of Washington, Seattle, WA, 3Lewis-Sigler Institute, Princeton University, Princeton, NJ and 4Department of Computer Science and Engineering, University of Washington, Seattle, WA, USA"},{"name":"1 Center for Biomembrane Research, Department of Biochemistry and Biophysics, Stockholm University, Sweden, 2Department of Genome Sciences, University of Washington, Seattle, WA, 3Lewis-Sigler Institute, Princeton University, Princeton, NJ and 4Department of Computer Science and Engineering, University of Washington, Seattle, WA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"John D.","family":"Storey","sequence":"additional","affiliation":[{"name":"1 Center for Biomembrane Research, Department of Biochemistry and Biophysics, Stockholm University, Sweden, 2Department of Genome Sciences, University of Washington, Seattle, WA, 3Lewis-Sigler Institute, Princeton University, Princeton, NJ and 4Department of Computer Science and Engineering, University of Washington, Seattle, WA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"William Stafford","family":"Noble","sequence":"additional","affiliation":[{"name":"1 Center for Biomembrane Research, Department of Biochemistry and Biophysics, Stockholm University, Sweden, 2Department of Genome Sciences, University of Washington, Seattle, WA, 3Lewis-Sigler Institute, Princeton University, Princeton, NJ and 4Department of Computer Science and Engineering, University of Washington, Seattle, WA, USA"},{"name":"1 Center for Biomembrane Research, Department of Biochemistry and Biophysics, Stockholm University, Sweden, 2Department of Genome Sciences, University of Washington, Seattle, WA, 3Lewis-Sigler Institute, Princeton University, Princeton, NJ and 4Department of Computer Science and Engineering, University of Washington, Seattle, WA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2009,2,4]]},"reference":[{"key":"2023013110165533900_B1","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1093\/biomet\/69.1.123","article-title":"Penalized maximum likelihood estimation in logistic regression and discrimination","volume":"69","author":"Anderson","year":"1982","journal-title":"Biometrika"},{"key":"2023013110165533900_B2","doi-asserted-by":"crossref","first-page":"1151","DOI":"10.1198\/016214501753382129","article-title":"Empirical bayes analysis of a microarray experiment","volume":"96","author":"Efron","year":"2001","journal-title":"J. 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