ABSTRACT
Genome scan studies for linkage analysis have been widely used to search candidate regions containing quantitative trait loci (QTLs). However, most genome scan studies for QTL mapping are analyzed without formal consideration of information provided by other genome scan studies of the same trait. When multiple genome scan studies of the same trait are available, we may increase the power to detect linkage between markers and QTLs by using information provided from all these studies. Methods that can formally integrate data from multiple genome scan studies are emerging as useful and powerful tools in the field of linkage analysis for QTL mapping. Marked heterogeneity can exist in multiple genome scan studies and pose daunting challenges in such analysis (see Chapter 4 by van Houwelingen and Lebrec). Different genome scan studies can use different genetic marker loci and marker maps, different statistical methods to test for linkage, and different sampling schemes. Furthermore, the QTL effect can vary across studies because of disparate environmental effects and population substructures. The combination of raw data from all studies with a well-designed pre-analysis procedure would be a preferred approach to overcome such difficulties. However, in many situations this is not feasible because only summary statistics, rather than the raw data, are available.
