title: Current analysis platforms and methods for detecting copy number variation.
abstract: Copy number variation (CNV), generated through duplication or deletion events that affect one or more loci, is widespread in the human genomes and is often associated with functional consequences that may include changes in gene expression levels or fusion of genes. Genome-wide association studies indicate that some disease phenotypes and physiological pathways might be impacted by CNV in a small number of characterized genomic regions. However, the pervasiveness and full impact of such variation remains unclear. Suitable analytic methods are needed to thoroughly mine human genomes for genomic structural variation, and to explore the interplay between observed CNV and disease phenotypes, but many medical researchers are unfamiliar with the features and nuances of recently developed technologies for detecting CNV. In this article, we evaluate a suite of commonly used and recently developed approaches to uncovering genome-wide CNVs and discuss the relative merits of each.
authors.affiliation: Biotechnology and Bioengineering Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA.
authors.forename: Wenli
authors.initials: W
authors.lastname: Li
authors.forename: Michael
authors.initials: M
authors.lastname: Olivier
mesh_terms: D000465:Algorithms; D055028:Comparative Genomic Hybridization / Q000379:methods*; D056915:DNA Copy Number Variations / Q000235:genetics*; D030541:Databases, Genetic; D015894:Genome, Human / Q000235:genetics*; D023281:Genomics / Q000379:methods*; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods*; D006801:Humans; D020641:Polymorphism, Single Nucleotide / Q000235:genetics*