{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,11]],"date-time":"2026-04-11T16:23:04Z","timestamp":1775924584904,"version":"3.50.1"},"reference-count":28,"publisher":"Oxford University Press (OUP)","issue":"5","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2013,3,1]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Motivation: Identification of bimodally expressed genes is an important task, as genes with bimodal expression play important roles in cell differentiation, signalling and disease progression. Several useful algorithms have been developed to identify bimodal genes from microarray data. Currently, no method can deal with data from next-generation sequencing, which is emerging as a replacement technology for microarrays.<\/jats:p><jats:p>Results: We present SIBER (systematic identification of bimodally expressed genes using RNAseq data) for effectively identifying bimodally expressed genes from next-generation RNAseq data. We evaluate several candidate methods for modelling RNAseq count data and compare their performance in identifying bimodal genes through both simulation and real data analysis. We show that the lognormal mixture model performs best in terms of power and robustness under various scenarios. We also compare our method with alternative approaches, including profile analysis using clustering and kurtosis (PACK) and cancer outlier profile analysis (COPA). Our method is robust, powerful, invariant to shifting and scaling, has no blind spots and has a sample-size-free interpretation.<\/jats:p><jats:p>Availability: The R package SIBER is available at the website http:\/\/bioinformatics.mdanderson.org\/main\/OOMPA:Overview.<\/jats:p><jats:p>Contact: kcoombes@mdanderson.org<\/jats:p><jats:p>Supplementary information: Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/bts713","type":"journal-article","created":{"date-parts":[[2013,1,10]],"date-time":"2013-01-10T05:46:12Z","timestamp":1357796772000},"page":"605-613","source":"Crossref","is-referenced-by-count":27,"title":["SIBER: systematic identification of bimodally expressed genes using RNAseq data"],"prefix":"10.1093","volume":"29","author":[{"given":"Pan","family":"Tong","sequence":"first","affiliation":[{"name":"1 Department of Bioinformatics and Computational Biology, The University of Texas M. D. Anderson Cancer Center, 2Biomathematics and Biostatistics, Graduate School of Biomedical Sciences, The University of Texas Health Science Center at Houston and 3Division of Biostatistics, The University of Texas Health Science Center at Houston, Houston, TX, USA"},{"name":"1 Department of Bioinformatics and Computational Biology, The University of Texas M. D. Anderson Cancer Center, 2Biomathematics and Biostatistics, Graduate School of Biomedical Sciences, The University of Texas Health Science Center at Houston and 3Division of Biostatistics, The University of Texas Health Science Center at Houston, Houston, TX, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yong","family":"Chen","sequence":"additional","affiliation":[{"name":"1 Department of Bioinformatics and Computational Biology, The University of Texas M. D. Anderson Cancer Center, 2Biomathematics and Biostatistics, Graduate School of Biomedical Sciences, The University of Texas Health Science Center at Houston and 3Division of Biostatistics, The University of Texas Health Science Center at Houston, Houston, TX, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiao","family":"Su","sequence":"additional","affiliation":[{"name":"1 Department of Bioinformatics and Computational Biology, The University of Texas M. D. Anderson Cancer Center, 2Biomathematics and Biostatistics, Graduate School of Biomedical Sciences, The University of Texas Health Science Center at Houston and 3Division of Biostatistics, The University of Texas Health Science Center at Houston, Houston, TX, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kevin R.","family":"Coombes","sequence":"additional","affiliation":[{"name":"1 Department of Bioinformatics and Computational Biology, The University of Texas M. D. Anderson Cancer Center, 2Biomathematics and Biostatistics, Graduate School of Biomedical Sciences, The University of Texas Health Science Center at Houston and 3Division of Biostatistics, The University of Texas Health Science Center at Houston, Houston, TX, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2013,1,9]]},"reference":[{"key":"2023051607331919300_bts713-B1","article-title":"Bimodal Gene Prediction Via Gap Maximisation","volume-title":"Proceedings of 2012 International Conference on Bioinformatics and Computational Biology","author":"Al-watban","year":"2012"},{"key":"2023051607331919300_bts713-B2","doi-asserted-by":"crossref","first-page":"R106","DOI":"10.1186\/gb-2010-11-10-r106","article-title":"Differential expression analysis for sequence count data","volume":"11","author":"Anders","year":"2010","journal-title":"Genome Biol."},{"key":"2023051607331919300_bts713-B3","doi-asserted-by":"crossref","first-page":"2008","DOI":"10.1101\/gr.133744.111","article-title":"Detecting differential usage of exons from RNA-Seq data","volume":"22","author":"Anders","year":"2012","journal-title":"Genome Res."},{"key":"2023051607331919300_bts713-B4","doi-asserted-by":"crossref","first-page":"3167","DOI":"10.1093\/emboj\/20.12.3167","article-title":"Cell signaling can direct either binary or graded transcriptional responses","volume":"20","author":"Biggar","year":"2001","journal-title":"EMBO J."},{"key":"2023051607331919300_bts713-B5","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1111\/j.2517-6161.1964.tb00553.x","article-title":"An analysis of transformations","volume":"26","author":"Box","year":"1964","journal-title":"J. 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