{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,7]],"date-time":"2025-02-07T00:40:30Z","timestamp":1738888830332,"version":"3.37.0"},"reference-count":36,"publisher":"Oxford University Press (OUP)","issue":"6","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2009,3,15]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Motivation: Genome analysis has become one of the most important tools for understanding the complex process of cancerogenesis. With increasing resolution of CGH arrays, the demand for computationally efficient algorithms arises, which are effective in the detection of aberrations even in very noisy data.<\/jats:p><jats:p>Results: We developed a rather simple, non-parametric technique of high computational efficiency for CGH array analysis that adopts a median absolute deviation concept for breakpoint detection, comprising median smoothing for pre-processing. The resulting algorithm has the potential to outperform any single smoothing approach as well as several recently proposed segmentation techniques. We show its performance through the application of simulated and real datasets in comparison to three other methods for array CGH analysis.<\/jats:p><jats:p>Implementation: Our approach is implemented in the R-language and environment for statistical computing (version 2.6.1 for Windows, R-project, 2007). The code is available at: http:\/\/www.iba.muni.cz\/~budinska\/msmad.html<\/jats:p><jats:p>Contact: \u00a0budinska@iba.muni.cz<\/jats:p><jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btp022","type":"journal-article","created":{"date-parts":[[2009,1,16]],"date-time":"2009-01-16T01:44:59Z","timestamp":1232070299000},"page":"703-713","source":"Crossref","is-referenced-by-count":7,"title":["MSMAD: a computationally efficient method for the analysis of noisy array CGH data"],"prefix":"10.1093","volume":"25","author":[{"given":"Eva","family":"Budinska","sequence":"first","affiliation":[{"name":"1 Institute of Biostatistics and Analyses, Masaryk University, Kamenice 126\/3, 625 00 Brno, Czech Republic and 2Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Auenbruggerplatz 2, 8036 Graz, Austria"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Eva","family":"Gelnarova","sequence":"additional","affiliation":[{"name":"1 Institute of Biostatistics and Analyses, Masaryk University, Kamenice 126\/3, 625 00 Brno, Czech Republic and 2Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Auenbruggerplatz 2, 8036 Graz, Austria"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Michael G.","family":"Schimek","sequence":"additional","affiliation":[{"name":"1 Institute of Biostatistics and Analyses, Masaryk University, Kamenice 126\/3, 625 00 Brno, Czech Republic and 2Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Auenbruggerplatz 2, 8036 Graz, Austria"},{"name":"1 Institute of Biostatistics and Analyses, Masaryk University, Kamenice 126\/3, 625 00 Brno, Czech Republic and 2Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Auenbruggerplatz 2, 8036 Graz, Austria"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2009,1,15]]},"reference":[{"key":"2023051209025018900_B1","doi-asserted-by":"crossref","first-page":"751","DOI":"10.1093\/bioinformatics\/btn003","article-title":"A segmental maximum a posteriori approach to genome-wide copy number profiling","volume":"24","author":"Andersson","year":"2008","journal-title":"Bioinformatics"},{"key":"2023051209025018900_B2","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1016\/j.cancergencyto.2005.11.017","article-title":"Complex chromosomal rearrangements in patients with chronic myeloid leukemia","volume":"168","author":"Babicka","year":"2006","journal-title":"Cancer Genet. 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