{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,23]],"date-time":"2026-03-23T19:01:01Z","timestamp":1774292461809,"version":"3.50.1"},"reference-count":15,"publisher":"Oxford University Press (OUP)","issue":"2","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2011,1,15]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Motivation: The pre-estimate of the proportion of null hypotheses (\u03c00) plays a critical role in controlling false discovery rate (FDR) in multiple hypothesis testing. However, hidden complex dependence structures of many genomics datasets distort the distribution of p-values, rendering existing \u03c00 estimators less effective.<\/jats:p><jats:p>Results: From the basic non-linear model of the q-value method, we developed a simple linear algorithm to probe local dependence blocks. We uncovered a non-static relationship between tests' p-values and their corresponding q-values that is influenced by data structure and \u03c00. Using an optimization framework, these findings were exploited to devise a Sliding Linear Model (SLIM) to more reliably estimate \u03c00 under dependence. When tested on a number of simulation datasets with varying data dependence structures and on microarray data, SLIM was found to be robust in estimating \u03c00 against dependence. The accuracy of its \u03c00 estimation suggests that SLIM can be used as a stand-alone tool for prediction of significant tests.<\/jats:p><jats:p>Availability: The R code of the proposed method is available at http:\/\/aspendb.uga.edu\/downloads for academic use.<\/jats:p><jats:p>Contact: \u00a0cjtsai@warnell.edu.edu<\/jats:p><jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btq650","type":"journal-article","created":{"date-parts":[[2010,11,20]],"date-time":"2010-11-20T01:23:45Z","timestamp":1290216225000},"page":"225-231","source":"Crossref","is-referenced-by-count":210,"title":["SLIM: a sliding linear model for estimating the proportion of true null hypotheses in datasets with dependence structures"],"prefix":"10.1093","volume":"27","author":[{"given":"Hong-Qiang","family":"Wang","sequence":"first","affiliation":[{"name":"1 Warnell School of Forestry and Natural Resources and 2Department of Genetics, University of Georgia, Athens, GA 30602, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lindsey K.","family":"Tuominen","sequence":"additional","affiliation":[{"name":"1 Warnell School of Forestry and Natural Resources and 2Department of Genetics, University of Georgia, Athens, GA 30602, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chung-Jui","family":"Tsai","sequence":"additional","affiliation":[{"name":"1 Warnell School of Forestry and Natural Resources and 2Department of Genetics, University of Georgia, Athens, GA 30602, USA"},{"name":"1 Warnell School of Forestry and Natural Resources and 2Department of Genetics, University of Georgia, Athens, GA 30602, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2010,11,18]]},"reference":[{"key":"2023012512171095000_B1","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1111\/j.2517-6161.1995.tb02031.x","article-title":"Controlling the false discovery rate: a practical and powerful approach to multiple testing","volume":"57","author":"Benjamini","year":"1995","journal-title":"J. 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