{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,29]],"date-time":"2026-03-29T12:37:20Z","timestamp":1774787840042,"version":"3.50.1"},"reference-count":26,"publisher":"Oxford University Press (OUP)","issue":"5","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2012,3,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Motivation: ChIPseq is rapidly becoming a common technique for investigating protein\u2013DNA interactions. However, results from individual experiments provide a limited understanding of chromatin structure, as various chromatin factors cooperate in complex ways to orchestrate transcription. In order to quantify chromtain interactions, it is thus necessary to devise a robust similarity metric applicable to ChIPseq data. Unfortunately, moving past simple overlap calculations to give statistically rigorous comparisons of ChIPseq datasets often involves arbitrary choices of distance metrics, with significance being estimated by computationally intensive permutation tests whose statistical power may be sensitive to non-biological experimental and post-processing variation.<\/jats:p>\n               <jats:p>Results: We show that it is in fact possible to compare ChIPseq datasets through the efficient computation of exact P-values for proximity. Our method is insensitive to non-biological variation in datasets such as peak width, and can rigorously model peak location biases by evaluating similarity conditioned on a restricted set of genomic regions (such as mappable genome or promoter regions).<\/jats:p>\n               <jats:p>Applying our method to the well-studied dataset of Chen et al. (2008), we elucidate novel interactions which conform well with our biological understanding. By comparing ChIPseq data in an asymmetric way, we are able to observe clear interaction differences between cofactors such as p300 and factors that bind DNA directly.<\/jats:p>\n               <jats:p>Availability: Source code is available for download at http:\/\/sonorus.princeton.edu\/IntervalStats\/IntervalStats.tar.gz<\/jats:p>\n               <jats:p>Contact: \u00a0ogt@cs.princeton.edu<\/jats:p>\n               <jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/bts009","type":"journal-article","created":{"date-parts":[[2012,1,20]],"date-time":"2012-01-20T02:49:12Z","timestamp":1327027752000},"page":"607-613","source":"Crossref","is-referenced-by-count":56,"title":["An effective statistical evaluation of ChIPseq dataset similarity"],"prefix":"10.1093","volume":"28","author":[{"given":"Maria","family":"D. Chikina","sequence":"first","affiliation":[{"name":"1 Department of Neurology, Mount Sinai School of Medicine, New York, NY 10029 and 2Lewis-Sigler Institute for Integrative Genomics, Department of Computer Science and Molecular Biology, Princeton University, Princeton, NJ 08540, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Olga","family":"G. Troyanskaya","sequence":"additional","affiliation":[{"name":"1 Department of Neurology, Mount Sinai School of Medicine, New York, NY 10029 and 2Lewis-Sigler Institute for Integrative Genomics, Department of Computer Science and Molecular Biology, Princeton University, Princeton, NJ 08540, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2012,1,19]]},"reference":[{"key":"2023012512193019300_B1","doi-asserted-by":"crossref","first-page":"456","DOI":"10.1186\/1471-2105-11-456","article-title":"Multivariate Hawkes process models of the occurrence of regulatory elements","volume":"11","author":"Carstensen","year":"2010","journal-title":"BMC Bioinformatics"},{"key":"2023012512193019300_B2","doi-asserted-by":"crossref","first-page":"1106","DOI":"10.1016\/j.cell.2008.04.043","article-title":"Integration of external signaling pathways with the core transcriptional network in embryonic stem cells","volume":"133","author":"Chen","year":"2008","journal-title":"Cell"},{"key":"2023012512193019300_B3","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1101\/gr.082800.108","article-title":"Global analysis of the insulator binding protein ctcf in chromatin barrier regions reveals demarcation of active and repressive domains","volume":"19","author":"Cuddapah","year":"2009","journal-title":"Genome Res."},{"key":"2023012512193019300_B4","doi-asserted-by":"crossref","first-page":"1429","DOI":"10.1039\/b906880e","article-title":"Scoring overlapping and adjacent signals from genome-wide chip and damid assays","volume":"5","author":"Fu","year":"2009","journal-title":"Mol. 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