Journal Article

On the frequency of copy number variants

Iuliana Ionita-Laza, Nan M. Laird, Benjamin A. Raby, Scott T. Weiss and Christoph Lange

in Bioinformatics

Volume 24, issue 20, pages 2350-2355
Published in print October 2008 | ISSN: 1367-4803
Published online August 2008 | e-ISSN: 1460-2059 | DOI: http://dx.doi.org/10.1093/bioinformatics/btn421
On the frequency of copy number variants

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Motivation: Estimating the frequency distribution of copy number variants (CNVs) is an important aspect of the effort to characterize this new type of genetic variation. Currently, most studies report a strong skew toward low-frequency CNVs. In this article, our goal is to investigate the frequencies of CNVs. We employ a two-step procedure for the CNV frequency estimation process. We use family information a posteriori to select only the most reliable CNV regions, i.e. those showing high rates of Mendelian transmission.

Results: Our results suggest that the current skew toward low-frequency CNVs may not be representative of the true frequency distribution, but may be due, among other reasons, to the non-negligible false negative rates that characterize CNV detection methods. Moreover, false positives are also likely, as low-frequency CNVs are hard to detect with small sample sizes and technologies that are not ideally suited for their detection. Without appropriate validation methods, such as incorporation of biologically relevant information (for example, in our case, the transmission of heritable CNVs from parents to offspring), it is difficult to assess the validity of specific CNVs, and even harder to obtain reliable frequency estimates.

Availability: Software implementing the methods described in this article is available for download at the following address: http://www.isites.harvard.edu/icb/icb.do?keyword=k36162

Contact: iionita@hsph.harvard.edu

Supplementary informantion: Supplementary data are available at Bioinformatics online.

Journal Article.  4638 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology

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