Genome-wide copy number profiling on high-density bacterial artificial chromosomes, single-nucleotide polymorphisms, and oligonucleotide microarrays: A platform comparison based on statistical power analysis

Jayne Y. Hehir-Kwa, Michael Egmont-Petersen, Irene M. Janssen, Dominique Smeets, Ad Geurts Van Kessel, Joris A. Veltman

Research output: Contribution to journalArticlepeer-review

82 Citations (Scopus)

Abstract

Recently, comparative genomic hybridization onto bacterial artificial chromosome (BAC) arrays (array-based comparative genomic hybridization) has proved to be successful for the detection of submicroscopic DNA copy-number variations in health and disease. Technological improvements to achieve a higher resolution have resulted in the generation of additional microarray platforms encompassing larger numbers of shorter DNA targets (oligonucleotides). Here, we present a novel method to estimate the ability of a microarray to detect genomic copy-number variations of different sizes and types (i.e. deletions or duplications). We applied our method, which is based on statistical power analysis, to four widely used high-density genomic microarray platforms. By doing so, we found that the high-density oligonucleotide platforms are superior to the BAC platform for the genome-wide detection of copy-number variations smaller than 1 Mb. The capacity to reliably detect single copy-number variations below 100 kb, however, appeared to be limited for all platforms tested. In addition, our analysis revealed an unexpected platform-dependent difference in sensitivity to detect a single copy-number loss and a single copy-number gain. These analyses provide a first objective insight into the true capacities and limitations of different genomic microarrays to detect and define DNA copy-number variations.

Original languageEnglish
Pages (from-to)1-11
Number of pages11
JournalDNA Research
Volume14
Issue number1
DOIs
Publication statusPublished - Mar 2007
Externally publishedYes

Keywords

  • Array CGH
  • Copy-number variation
  • Microdeletion
  • Molecular cytogenetics
  • Power analysis

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