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 :
بازگشت