Dataset Information

Hidden copy number variation in the HapMap population.

ABSTRACT: Recently, the extent of copy number variation (CNV) throughout the genome has been shown to be far greater than previously thought. Further, it has been demonstrated that specific copy number variable regions (CNVRs) are associated with particular diseases, suggesting that these genetic variations may have an important biological role. Hence, calling CNVRs and subsequently classifying samples as "losses" or "gains" is of great interest. A number of papers have been published containing classifications of CNVs, and here we show how the presence of pedigree information can be used for assessing the performance of those classification methods. In this article, by examining CNV classifications made in the HapMap samples, we show that estimates of the number of false-positive classifications per individual made by current approaches can be determined. Moreover, commonplace technologies for determining the locations of CNVRs aggregate information across the maternal and paternal chromosomes at the locus of interest. Here, we show that copy number variation on each chromosome can be inferred and, in particular, we discuss the existence of a class of CNVs that are inevitably misclassified and give an estimate of their prevalence. Although our focus is not on the development of calling algorithms per se, we describe and provide an example of how our model might be incorporated into the initial classification procedure to produce more robust results. Finally, we discuss how this methodology might be applied to future studies to obtain better estimates of the extent of CNV across the genome.

SUBMITTER: Marioni JC

PROVIDER: S-EPMC2481329 | biostudies-literature | 2008 Jul

REPOSITORIES: biostudies-literature

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Publications

Hidden copy number variation in the HapMap population.

Marioni John C JC White Michael M Tavaré Simon S Lynch Andrew G AG

Proceedings of the National Academy of Sciences of the United States of America 20080715 29

Recently, the extent of copy number variation (CNV) throughout the genome has been shown to be far greater than previously thought. Further, it has been demonstrated that specific copy number variable regions (CNVRs) are associated with particular diseases, suggesting that these genetic variations may have an important biological role. Hence, calling CNVRs and subsequently classifying samples as "losses" or "gains" is of great interest. A number of papers have been published containing classific ...[more]

PMID: 18632583

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Project description:Copy number variation (CNV) is a major genetic polymorphism contributing to genetic diversity and human evolution. Clinical application of CNVs for diagnostic purposes largely depends on sufficient population CNV data for accurate interpretation. CNVs from general population in currently available databases help classify CNVs of uncertain clinical significance, and benign CNVs. Earlier studies of CNV distribution in several populations worldwide showed that a significant fraction of CNVs are population specific. In this study, we characterized and analyzed CNVs in 3,017 unrelated Thai individuals genotyped with the Illumina Human610, Illumina HumanOmniexpress, or Illumina HapMap550v3 platform. We employed hidden Markov model and circular binary segmentation methods to identify CNVs, extracted 23,458 CNVs consistently identified by both algorithms, and cataloged these high confident CNVs into our publicly available Thai CNV database. Analysis of CNVs in the Thai population identified a median of eight autosomal CNVs per individual. Most CNVs (96.73%) did not overlap with any known chromosomal imbalance syndromes documented in the DECIPHER database. When compared with CNVs in the 11 HapMap3 populations, CNVs found in the Thai population shared several characteristics with CNVs characterized in HapMap3. Common CNVs in Thais had similar frequencies to those in the HapMap3 populations, and all high frequency CNVs (>20%) found in Thai individuals could also be identified in HapMap3. The majorities of CNVs discovered in the Thai population, however, were of low frequency, or uniquely identified in Thais. When performing hierarchical clustering using CNV frequencies, the CNV data were clustered into Africans, Europeans, and Asians, in line with the clustering performed with single nucleotide polymorphism (SNP) data. As CNV data are specific to origin of population, our population-specific reference database will serve as a valuable addition to the existing resources for the investigation of clinical significance of CNVs in Thais and related ethnicities.

Dataset Information

Hidden copy number variation in the HapMap population.

Publications

Hidden copy number variation in the HapMap population.

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