{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,8]],"date-time":"2026-04-08T21:05:28Z","timestamp":1775682328730,"version":"3.50.1"},"reference-count":39,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2023,2,16]],"date-time":"2023-02-16T00:00:00Z","timestamp":1676505600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"European Commission","award":["739574"],"award-info":[{"award-number":["739574"]}]},{"name":"European Commission","award":["N2-0171"],"award-info":[{"award-number":["N2-0171"]}]},{"name":"Republic of Slovenia (Investment funding of the Republic of Slovenia and the European Union of the European Regional Development Fund)","award":["739574"],"award-info":[{"award-number":["739574"]}]},{"name":"Republic of Slovenia (Investment funding of the Republic of Slovenia and the European Union of the European Regional Development Fund)","award":["N2-0171"],"award-info":[{"award-number":["N2-0171"]}]},{"name":"Slovenian Research Agency (ARRS)","award":["739574"],"award-info":[{"award-number":["739574"]}]},{"name":"Slovenian Research Agency (ARRS)","award":["N2-0171"],"award-info":[{"award-number":["N2-0171"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>Copy number variation (CNV) is a form of structural variation in the human genome that provides medical insight into complex human diseases; while whole-genome sequencing is becoming more affordable, whole-exome sequencing (WES) remains an important tool in clinical diagnostics. Because of its discontinuous nature and unique characteristics of sparse target-enrichment-based WES data, the analysis and detection of CNV peaks remain difficult tasks. The Savitzky\u2013Golay (SG) smoothing is well known as a fast and efficient smoothing method. However, no study has documented the use of this technique for CNV peak detection. It is well known that the effectiveness of the classical SG filter depends on the proper selection of the window length and polynomial degree, which should correspond with the scale of the peak because, in the case of peaks with a high rate of change, the effectiveness of the filter could be restricted. Based on the Savitzky\u2013Golay algorithm, this paper introduces a novel adaptive method to smooth irregular peak distributions. The proposed method ensures high-precision noise reduction by dynamically modifying the results of the prior smoothing to automatically adjust parameters. Our method offers an additional feature extraction technique based on density and Euclidean distance. In comparison to classical Savitzky\u2013Golay filtering and other peer filtering methods, the performance evaluation demonstrates that adaptive Savitzky\u2013Golay filtering performs better. According to experimental results, our method effectively detects CNV peaks across all genomic segments for both short and long tags, with minimal peak height fidelity values (i.e., low estimation bias). As a result, we clearly demonstrate how well the adaptive Savitzky\u2013Golay filtering method works and how its use in the detection of CNV peaks can complement the existing techniques used in CNV peak analysis.<\/jats:p>","DOI":"10.3390\/info14020128","type":"journal-article","created":{"date-parts":[[2023,2,16]],"date-time":"2023-02-16T02:52:56Z","timestamp":1676515976000},"page":"128","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Adaptive Savitzky\u2013Golay Filters for Analysis of Copy Number Variation Peaks from Whole-Exome Sequencing Data"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6497-6481","authenticated-orcid":false,"given":"Peter Juma","family":"Ochieng","sequence":"first","affiliation":[{"name":"Institute of Informatics, University of Szeged, 2 \u00c1rp\u00e1d t\u00e9r, H-6720 Szeged, Hungary"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0515-117X","authenticated-orcid":false,"given":"Zolt\u00e1n","family":"Mar\u00f3ti","sequence":"additional","affiliation":[{"name":"Albert Szent-Gy\u00f6rgyi Health Centre, Department of Pediatrics and Pediatric Health Center, University of Szeged, H-6725 Szeged, Hungary"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9459-912X","authenticated-orcid":false,"given":"J\u00f3zsef","family":"Dombi","sequence":"additional","affiliation":[{"name":"Institute of Informatics, University of Szeged, 2 \u00c1rp\u00e1d t\u00e9r, H-6720 Szeged, Hungary"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7547-1128","authenticated-orcid":false,"given":"Mikl\u00f3s","family":"Kr\u00e9sz","sequence":"additional","affiliation":[{"name":"InnoRenew CoE, Livade 6, 6310 Izola, Slovenia"},{"name":"Andrej Maru\u0161i\u010d Institute, University of Primorska, Muzejski trg 2, 6000 Koper, Slovenia"},{"name":"Department of Applied Informatics, University of Szeged, Boldogasszony sgt. 6, H-6725 Szeged, Hungary"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3820-9777","authenticated-orcid":false,"given":"J\u00f3zsef","family":"B\u00e9k\u00e9si","sequence":"additional","affiliation":[{"name":"Institute of Informatics, University of Szeged, 2 \u00c1rp\u00e1d t\u00e9r, H-6720 Szeged, Hungary"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0419-2009","authenticated-orcid":false,"given":"Tibor","family":"Kalm\u00e1r","sequence":"additional","affiliation":[{"name":"Albert Szent-Gy\u00f6rgyi Health Centre, Department of Pediatrics and Pediatric Health Center, University of Szeged, H-6725 Szeged, Hungary"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,2,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Zhang, L., Bai, W., Yuan, N., and Du, Z. 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