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Human Molecular Genetics 2007 16(R2):R168-R173; doi:10.1093/hmg/ddm241
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© The Author 2007. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Copy-number variation in control population cohorts

Dalila Pinto1,2,{dagger}, Christian Marshall1,2,{dagger}, Lars Feuk1,2 and Stephen W. Scherer1,2,*

1 The Centre for Applied Genomics and 2 Program in Genetics and Genomic Biology, The Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada

* To whom correspondence should be addressed at: The Centre for Applied Genomics, The Hospital for Sick Children, 14th Floor, Toronto Medical Discovery Tower/MaRS Discovery District, 101 College Street, Room 14-701, Ontario, Canada, M5G 1L7. Tel: +1 4168137613; Fax: +1 4168138319; Email: steve{at}genet.sickkids.on.ca

Received August 2, 2007; Revised August 2, 2007; Accepted August 22, 2007

Copy-number variation (CNV) is the most prevalent type of structural variation in the human genome, and contributes significantly to genetic heterogeneity. It has already been recognized that some CNVs can contribute to human phenotype, including rare genomic disorders and Mendelian diseases. Other CNVs are now amenable to genome-wide association studies so that their influence on human phenotypic diversity and disease susceptibility may soon be more readily determined. Population studies and reference databases for control and disease-associated samples are required to provide an information resource about CNV frequencies and their relative contribution to phenotypic outcomes. The relatively high cost of screening individual samples has tended to limit the number of controls assayed, and use of the data has often been hampered by the variety of technology platforms and analysis techniques. As a result, there is still a paucity of data on population frequency and distribution of CNVs, particularly for those that are rare. Here, we provide an example of how to discover new CNVs from existing genotype data from large-scale genetic epidemiological studies. We also discuss the need to expand surveys of CNV in different population-based cohorts and to apply the information to studies of human variation and disease.


{dagger} The authors wish it to be known that, in their opinion, the first two authors should be regarded as joint First Authors.


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