Maciej Sykulski, T. Gambin, M. Bartnik, K. Derwinska, B. Wiśniowiecka-Kowalnik, P. Stankiewicz, A. Gambin
{"title":"用于稀有CNVs检测的高效多样本aCGH分析","authors":"Maciej Sykulski, T. Gambin, M. Bartnik, K. Derwinska, B. Wiśniowiecka-Kowalnik, P. Stankiewicz, A. Gambin","doi":"10.1109/BIBM.2011.38","DOIUrl":null,"url":null,"abstract":"We propose a novel multiple sample aCGH analysis methodology aiming in rare Copy-Number Variations (CNVs) detection. Our method is tested on exon targeted aCGH array of 366 patients affected with developmental delay/intellectual disability, epilepsy, or autism. The proposed algorithms can be applied as a post -- processing filtering to any given segmentation method. Thanks to the additional information obtained from multiple samples, we could efficiently detect significant segments corresponding to rare CNVs responsible for pathogenic changes. More detailed description of the method is available in Supplementary Materials at: http://bioputer.mimuw.edu.pl/acgh.","PeriodicalId":73283,"journal":{"name":"IEEE International Conference on Bioinformatics and Biomedicine workshops. IEEE International Conference on Bioinformatics and Biomedicine","volume":"43 1","pages":"406-409"},"PeriodicalIF":0.0000,"publicationDate":"2011-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Efficient Multiple Samples aCGH Analysis for Rare CNVs Detection\",\"authors\":\"Maciej Sykulski, T. Gambin, M. Bartnik, K. Derwinska, B. Wiśniowiecka-Kowalnik, P. Stankiewicz, A. Gambin\",\"doi\":\"10.1109/BIBM.2011.38\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We propose a novel multiple sample aCGH analysis methodology aiming in rare Copy-Number Variations (CNVs) detection. Our method is tested on exon targeted aCGH array of 366 patients affected with developmental delay/intellectual disability, epilepsy, or autism. The proposed algorithms can be applied as a post -- processing filtering to any given segmentation method. Thanks to the additional information obtained from multiple samples, we could efficiently detect significant segments corresponding to rare CNVs responsible for pathogenic changes. More detailed description of the method is available in Supplementary Materials at: http://bioputer.mimuw.edu.pl/acgh.\",\"PeriodicalId\":73283,\"journal\":{\"name\":\"IEEE International Conference on Bioinformatics and Biomedicine workshops. IEEE International Conference on Bioinformatics and Biomedicine\",\"volume\":\"43 1\",\"pages\":\"406-409\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-11-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE International Conference on Bioinformatics and Biomedicine workshops. IEEE International Conference on Bioinformatics and Biomedicine\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/BIBM.2011.38\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE International Conference on Bioinformatics and Biomedicine workshops. IEEE International Conference on Bioinformatics and Biomedicine","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BIBM.2011.38","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Efficient Multiple Samples aCGH Analysis for Rare CNVs Detection
We propose a novel multiple sample aCGH analysis methodology aiming in rare Copy-Number Variations (CNVs) detection. Our method is tested on exon targeted aCGH array of 366 patients affected with developmental delay/intellectual disability, epilepsy, or autism. The proposed algorithms can be applied as a post -- processing filtering to any given segmentation method. Thanks to the additional information obtained from multiple samples, we could efficiently detect significant segments corresponding to rare CNVs responsible for pathogenic changes. More detailed description of the method is available in Supplementary Materials at: http://bioputer.mimuw.edu.pl/acgh.