1. ¹Department of Biostatistics and Epidemiology, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
2. ²Department of Biostatistics, Vanderbilt University School of Medicine, Nashville, TN, USA
3. ³Center for Human Genetics Research, Vanderbilt University School of Medicine, Nashville, TN, USA
4. ⁴Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA

Correspondence: Dr M Li, Department of Biostatistics and Epidemiology, University of Pennsylvania School of Medicine, 624 Blockley Hall, Philadelphia, PA 19104, USA. Tel: +1 215 746 3916; Fax: +1 215 573 4865; E-mail: mingyao@mail.med.upenn.edu

⁵These authors contributed equally to this work.

Received 19 April 2007; Revised 30 November 2007; Accepted 20 December 2007; Published online 6 February 2008.

Abstract

Genome-wide association (GWA) studies for complex human diseases are now feasible. Many GWA studies rely on commercial SNP chips, for which a common evaluation criterion is global coverage of the genome. Although providing an overall evaluation of an SNP chip, the global coverage does not tell us how the coverage varies across the genome, an important feature that should be taken into consideration, as coverage variation often results in power variation and potentially biased search in subsequent association analysis. To achieve a fuller understanding of SNP chip coverage, we conducted detailed evaluation of coverage, including (1) a map of local coverage – calculated over small consecutive genomic regions and (2) gene coverage – calculated for each known gene in the genome. These evaluations can reveal the degree of variation of each SNP chip in covering the genome and can facilitate SNP chip comparisons at a finer scale.