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Analyzing copy number variation using SNP array data: protocols for calling CNV and association tests.

TitleAnalyzing copy number variation using SNP array data: protocols for calling CNV and association tests.
Publication TypeJournal Article
Year of Publication2013
AuthorsLin, C-F, Naj, AC, San Wang, L-
JournalCurr Protoc Hum Genet
PaginationUnit 1.27.
Date Published2013 Oct 18
KeywordsAlgorithms, DNA Copy Number Variations, Gene Frequency, Genome-Wide Association Study, Genotyping Techniques, High-Throughput Nucleotide Sequencing, Humans, Oligonucleotide Array Sequence Analysis, Polymorphism, Single Nucleotide

High-density SNP genotyping technology provides a low-cost, effective tool for conducting Genome Wide Association (GWA) studies. The wide adoption of GWA studies has indeed led to discoveries of disease- or trait-associated SNPs, some of which were subsequently shown to be causal. However, the nearly universal shortcoming of many GWA studies--missing heritability--has prompted great interest in searching for other types of genetic variation, such as copy number variation (CNV). Certain CNVs have been reported to alter disease susceptibility. Algorithms and tools have been developed to identify CNVs using SNP array hybridization intensity data. Such an approach provides an additional source of data with almost no extra cost. In this unit, we demonstrate the steps for calling CNVs from Illumina SNP array data using PennCNV and performing association analysis using R and PLINK.

Alternate JournalCurr Protoc Hum Genet
PubMed ID24510649
PubMed Central IDPMC4015338
Grant ListU01 AG032984 / AG / NIA NIH HHS / United States
U24 AG041689 / AG / NIA NIH HHS / United States