1. ¹Laboratory of Cancer Genetics, Van Andel Research Institute, Grand Rapids, MI, USA
2. ²Department of Human and Clinical Genetics, Leiden University Medical Center (LUMC), Leiden, The Netherlands
3. ³Department of Oncology, Lund University, Lund, Sweden
4. ⁴The Dr John T Macdonald Foundation Center for Medical Genetics, Miller School of Medicine, University of Miami, Miami, FL, USA
5. ⁵Department of Molecular Medicine and Surgery, Karolinska Institutet, Karolinska University Hospital Solna, Stockholm, Sweden

Correspondence: Dr J Schoumans, Department of Molecular Medicine and Surgery, Karolinska Institute, Karolinska University Hospital Solna, Stockholm, Sweden. Tel: +46 8 51770453; Fax: +46 8 51773620; E-mail: Jacqueline.schoumans@ki.se

Received 25 September 2007; Revised 17 December 2007; Accepted 11 January 2008; Published online 20 February 2008.

Abstract

For several decades etiological diagnosis of patients with idiopathic mental retardation (MR) and multiple congenital anomalies (MCA) has relied on chromosome analysis by karyotyping. Conventional karyotyping allows a genome-wide detection of chromosomal abnormalities but has a limited resolution. Recently, array-based comparative genomic hybridization (array CGH) technologies have been developed to evaluate DNA copy-number alterations across the whole-genome at a much higher resolution. It has proven to be an effective tool for detection of submicroscopic chromosome abnormalities causing congenital disorders and has recently been adopted for clinical applications. Here, we investigated four high-density array platforms with a theoretical resolution 100 kb: 33K tiling path BAC array, 500K Affymetrix SNP array, 385K NimbleGen oligonucleotide array and 244K Agilent oligonucleotide array for their robustness and implementation in our diagnostic setting. We evaluated the practical performance based on the detection of 10 previously characterized abnormalities whose size ranged from 100 kb to 3 Mb. Furthermore, array data analysis was performed using four computer programs developed for each corresponding platform to test their effective ability of reliable copy-number detection and their user-friendliness. All tested platforms provided sensitive performances, but our experience showed that accurate and user-friendly computer programs are of crucial importance for reliable copy-number detection.