DocumentCode
3645124
Title
Efficient Multiple Samples aCGH Analysis for Rare CNVs Detection
Author
Maciej Sykulski;Tomasz Gambin;Magdalena Bartnik;Katarzyna Derwinska;Barbara Wisniowiecka-Kowalnik;Pawel Stankiewicz;Anna Gambin
Author_Institution
Inst. of Inf., Univ. of Warsaw, Warsaw, Poland
fYear
2011
Firstpage
406
Lastpage
409
Abstract
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.
Keywords
"Bioinformatics","Genomics","Arrays","Probes","Databases","Autism"
Publisher
ieee
Conference_Titel
Bioinformatics and Biomedicine (BIBM), 2011 IEEE International Conference on
Print_ISBN
978-1-4577-1799-4
Type
conf
DOI
10.1109/BIBM.2011.38
Filename
6120475
Link To Document