Performance assessment of copy number microarray platforms using a spike-in experiment

Eitan Halper-Stromberg, Laurence Frelin, Ingo Ruczinski, Robert Scharpf, Chunfa Jie, Benilton Carvalho, Haiping Hao, Kurt Hetrick, Anne Jedlicka, Amanda Dziedzic, Kim Doheny, Alan F. Scott, Steve Baylin, Jonathan Pevsner, Forrest Spencer, Rafael A. Irizarry

Research output: Contribution to journalArticlepeer-review

Abstract

Motivation: Changes in the copy number of chromosomal DNA segments [copy number variants (CNVs)] have been implicated in human variation, heritable diseases and cancers. Microarray-based platforms are the current established technology of choice for studies reporting these discoveries and constitute the benchmark against which emergent sequence-based approaches will be evaluated. Research that depends on CNV analysis is rapidly increasing, and systematic platform assessments that distinguish strengths and weaknesses are needed to guide informed choice. Results: We evaluated the sensitivity and specificity of six platforms, provided by four leading vendors, using a spike-in experiment. NimbleGen and Agilent platforms outperformed Illumina and Affymetrix in accuracy and precision of copy number dosage estimates. However, Illumina and Affymetrix algorithms that leverage single nucleotide polymorphism (SNP) information make up for this disadvantage and perform well at variant detection. Overall, the NimbleGen 2.1M platform outperformed others, but only with the use of an alternative data analysis pipeline to the one offered by the manufacturer.

Original languageEnglish (US)
Article numberbtr106
Pages (from-to)1052-1060
Number of pages9
JournalBioinformatics
Volume27
Issue number8
DOIs
StatePublished - Apr 2011

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

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