Copy-number-variation and copy-number-alteration region detection by cumulative plots

BMC Bioinformatics. 2009 Jan 30;10 Suppl 1(Suppl 1):S67. doi: 10.1186/1471-2105-10-S1-S67.

Abstract

Background: Regions with copy number variations (in germline cells) or copy number alteration (in somatic cells) are of great interest for human disease gene mapping and cancer studies. They represent a new type of mutation and are larger-scaled than the single nucleotide polymorphisms. Using genotyping microarray for copy number variation detection has become standard, and there is a need for improving analysis methods.

Results: We apply the cumulative plot to the detection of regions with copy number variation/alteration, on samples taken from a chronic lymphocytic leukemia patient. Two sets of whole-genome genotyping of 317 k single nucleotide polymorphisms, one from the normal cell and another from the cancer cell, are analyzed. We demonstrate the utility of cumulative plot in detecting a 9 Mb (9 x 10(6) bases) hemizygous deletion and 1 Mb homozygous deletion on chromosome 13. We also show the possibility to detect smaller copy number variation/alteration regions below the 100 kb range.

Conclusion: As a graphic tool, the cumulative plot is an intuitive and a scale-free (window-less) way for detecting copy number variation/alteration regions, especially when such regions are small.

MeSH terms

  • Algorithms
  • Gene Dosage / genetics*
  • Genetic Variation*
  • Genome, Human
  • Genotype
  • Homozygote
  • Humans
  • Mutation