Multiple samples aCGH analysis for rare CNVs detection

Maciej Sykulski , Tomasz Gambin , Magdalena Bartnik , Katarzyna Derwińska , Barbara Wiśniowiecka-Kowalnik , Paweł Stankiewicz , Anna Gambin


Background: DNA copy number variations (CNV) constitute an important source of genetic variability. The standard method used for CNV detection is array comparative genomic hybridization (aCGH). Results: We propose a novel multiple sample aCGH analysis methodology aiming in rare CNVs detection. In contrast to the majority of previous approaches, which deal with cancer datasets, we focus on constitutional genomic abnormalities identified in a diverse spectrum of diseases in human. 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. Conclusions: Thanks to the additional information obtained from multiple samples, we could efficiently detect significant segments corresponding to rare CNVs responsible for pathogenic changes. The robust statistical framework applied in our method enables to eliminate the influence of widespread technical artifact termed 'waves'.
Author Maciej Sykulski - [University of Warsaw, Institute of Informatics]
Maciej Sykulski,,
- University of Warsaw, Institute of Informatics
, Tomasz Gambin (FEIT / IN)
Tomasz Gambin,,
- The Institute of Computer Science
, Magdalena Bartnik - [Instytut Matki I Dziecka]
Magdalena Bartnik,,
, Katarzyna Derwińska - [Instytut Matki I Dziecka]
Katarzyna Derwińska,,
, Barbara Wiśniowiecka-Kowalnik - [Instytut Matki I Dziecka]
Barbara Wiśniowiecka-Kowalnik,,
, Paweł Stankiewicz - [Instytut Matki I Dziecka]
Paweł Stankiewicz,,
, Anna Gambin - [University of Warsaw, Institute of Informatics]
Anna Gambin,,
- University of Warsaw, Institute of Informatics
Journal seriesJournal of Clinical Bioinformatics, ISSN 2043-9113
Issue year2013
Publication size in sheets0.5
ASJC Classification2718 Health Informatics
Languageen angielski
Score (nominal)0
Score sourcejournalList
ScoreMinisterial score = 0.0, 27-08-2020, ArticleFromJournal
Ministerial score (2013-2016) = 0.0, 27-08-2020, ArticleFromJournal
Publication indicators WoS Citations = 0; Scopus Citations = 2; GS Citations = 6.0; Scopus SNIP (Source Normalised Impact per Paper): 2013 = 0.782
Citation count*6 (2020-08-30)
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* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.
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