One way of increasing power for linkage studies is to use more closely spaced markers, which is now possible with the advent of high-throughput technology for large scale SNP genotyping. Simulation studies have indicated that SNPs can offer equal or superior power to detect linkage compared with low-density microsatellite maps [2]. Recently, several studies have demonstrated empirically that denser SNP maps can improve gene localization and increase power to detect signals for complex traits, particularly in regions characterized by poor coverage or information content [3-5]. However, all of these studies used nonparametric linkage methods, and it is not known how SNPs will perform using other approaches, such as variance components, which can be more powerful than relative pair-based approaches. Thus, the purpose of this study was to compare variance components linkage results in detecting quantitative trait loci (QTLs) for alcoholism using different density marker maps.
