Aarhus Universitets segl

Alexander Schmitz

Performance Comparison of Affymetrix SNP6.0 and Cytogenetic 2.7M Whole-Genome Microarrays in Complex Cancer Samples

Publikation: Bidrag til tidsskrift/Konferencebidrag i tidsskrift /Bidrag til avisTidsskriftartikelForskningpeer review

  • J S Bødker, Aalborg Universitet, Danmark
  • C Gyrup
  • ,
  • P Johansen, Aalborg Universitet, Danmark
  • A Schmitz
  • J Madsen, Aalborg Universitet, Danmark
  • H E Johnsen, Aalborg Universitet, Danmark
  • M Bøgsted
  • K Dybkær, Aalborg Universitet, Danmark
  • M Nyegaard, Danmark
The Affymetrix cytogenetic 2.7M whole-genome microarray (Cyto2.7M) detects genomic aberrations. The Cyto2.7M array has increased coverage in regions with cancer-related genes, ∼4-fold reduced processing time, and 5-fold reduced input requirements (100 ng) compared to the commonly used Affymetrix SNP6.0 genome-wide microarray (SNP6.0). We set out to compare the performance of these microarrays on cancer samples containing complex genomic changes. We analyzed genomic DNA from 8 lymphoma samples and 1 blood sample using both SNP6.0 and Cyto2.7M microarrays. We compared the arrays with respect to 4 parameters, including detection of copy number variations (CNV), CNV boundaries, the actual copy number (CN) assigned to the aberrations, and loss of heterozygosity. The CN state of selected regions was validated by quantitative PCR. Very high consistency between arrays on all parameters tested was observed, hence only 30 of 224 aberrations disagreed on the CN state, corresponding to a total of ∼12 Mb or 0.06% of the analyzed base pairs. Thus, the SNP6.0 and Cyto2.7M arrays are equally well suited to detect genomic aberrations in complex samples such as cancer samples. With reduced processing time and lower input requirements, the Cyto2.7M array enables genomic analysis of samples where only limited DNA is available.
TidsskriftCytogenetic and Genome Research
Sider (fra-til)80-87
Antal sider7
StatusUdgivet - 2013

Se relationer på Aarhus Universitet Citationsformater

ID: 51173120