Current analysis platforms and methods for detecting copy number variation
Author(s) -
Wenli Li,
Michael Olivier
Publication year - 2012
Publication title -
physiological genomics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.078
H-Index - 112
eISSN - 1531-2267
pISSN - 1094-8341
DOI - 10.1152/physiolgenomics.00082.2012
Subject(s) - copy number variation , biology , genome , gene duplication , phenotype , structural variation , human genome , genome wide association study , genetics , variation (astronomy) , computational biology , gene , genomics , gene dosage , copy number analysis , genetic variation , evolutionary biology , single nucleotide polymorphism , gene expression , genotype , physics , astrophysics
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.
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