Association Tests and Software for Copy Number Variant Data

Hum Genomics. 2009 Jan;3(2):191-4. doi: 10.1186/1479-7364-3-2-191.

Abstract

Recent studies have suggested that copy number variation (CNV) significantly contributes to genetic predisposition to several common disorders. These findings, combined with the imperfect tagging of CNVs by single nucleotide polymorphisms (SNPs), have motivated the development of association studies directly targeting CNVs. Several assays, including comparative genomic hybridisation arrays, SNP genotyping arrays, or DNA quantification through real-time polymerase chain reaction analysis, allow direct assessment of CNV status in cohorts sufficiently large to provide adequate statistical power for association studies. When analysing data provided by these assays, association tests for CNV data are not fundamentally different from SNP-based association tests. The main difference arises when the quality of the CNV assay is not sufficient to convert unequivocally the raw measurement into discrete calls - a common issue, given the technological limitations of current CNV assays. When this is the case, association tests are more appropriately based on the raw continuous measurement provided by the CNV assay, instead of potentially inaccurate discrete calls, thus motivating the development of new statistical methods. Here, the programs available for CNV association testing for case control or family data are reviewed, using either discrete calls or raw continuous data.

MeSH terms

  • Algorithms
  • Gene Dosage
  • Genetic Variation*
  • Genome-Wide Association Study*
  • Humans
  • Polymorphism, Single Nucleotide
  • Software*