Diagnostic Interpretation of Array Data Using Public Databases and Internet Sources

Nicole de Leeuw*, Trijnie Dijkhuizen, Jayne Y. Hehir-Kwa, Nigel P. Carter, Lars Feuk, Helen V. Firth, Robert M. Kuhn, David H. Ledbetter, Christa Lese Martin, Conny M. A. van Ravenswaaij-Arts, Steven W. Scherer, Soheil Shams, Steven Van Vooren, Rolf Sijmons, Morris Swertz, Ros Hastings

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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Abstract

The range of commercially available array platforms and analysis software packages is expanding and their utility is improving, making reliable detection of copy-number variants (CNVs) relatively straightforward. Reliable interpretation of CNV data, however, is often difficult and requires expertise. With our knowledge of the human genome growing rapidly, applications for array testing continuously broadening, and the resolution of CNV detection increasing, this leads to great complexity in interpreting what can be daunting data. Correct CNV interpretation and optimal use of the genotype information provided by single-nucleotide polymorphism probes on an array depends largely on knowledge present in various resources. In addition to the availability of host laboratories' own datasets and national registries, there are several public databases and Internet resources with genotype and phenotype information that can be used for array data interpretation. With so many resources now available, it is important to know which are fit-for-purpose in a diagnostic setting. We summarize the characteristics of the most commonly used Internet databases and resources, and propose a general data interpretation strategy that can be used for comparative hybridization, comparative intensity, and genotype-based array data. Hum Mutat 33: 930-940, 2012. (C) 2012 Wiley Periodicals, Inc.

Original languageEnglish
Pages (from-to)930-940
Number of pages11
JournalHuman Mutation
Volume33
Issue number6
DOIs
Publication statusPublished - Jun-2012

Keywords

  • array
  • classification
  • CNV
  • database
  • data interpretation
  • diagnostic
  • genome wide
  • HUMAN PHENOTYPE ONTOLOGY
  • COPY NUMBER
  • HUMAN GENOME
  • STRUCTURAL VARIATION
  • VARIANTS

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