A novel signal processing approach for the detection of copy number variations in the human genome. | Zendy

Catherine Stamoulis | Zendy; Rebecca A. Betensky | Zendy

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A novel signal processing approach for the detection of copy number variations in the human genome.

Author(s) -

Catherine Stamoulis,

Rebecca A. Betensky

Publication year - 2011

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btr402

Subject(s) - copy number variation , computer science , human genome , single nucleotide polymorphism , false discovery rate , computational biology , robustness (evolution) , biology , genetics , genome , gene , genotype

Human genomic variability occurs at different scales, from single nucleotide polymorphisms (SNPs) to large DNA segments. Copy number variations (CNVs) represent a significant part of our genetic heterogeneity and have also been associated with many diseases and disorders. Short, localized CNVs, which may play an important role in human disease, may be undetectable in noisy genomic data. Therefore, robust methodologies are needed for their detection. Furthermore, for meaningful identification of pathological CNVs, estimation of normal allelic aberrations is necessary.

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