Meta-analysis of genome-wide linkage studies: optimal bin width for the GSMA M.Y. Ng, C.M. Lewis Department of Medical and Molecular Genetics, King’s College London School of Medicine, UK. Linkage studies of common complex disorders have low power to detect linked regions. Genome search meta-analysis method (GSMA) pools results from different linkage scans to identify novel linked regions or confirm susceptibility regions. The genome is divided into bins of approximately equal width. For each study, the strongest linkage evidence within each bin is identified and used to rank the bins. Each bin’s rank is then summed across studies and assessed by Monte Carlo simulation. A dominant disease locus model with sibling relative risk (λs) of 1.15 and 1.3 located at either 10cM or 80cM on a 180cM chromosome was simulated. We compared the power to detect linkage between bin widths of 20cM, 30cM and 40cM. We determined power to detect suggestive evidence for linkage, which controls for different numbers of bins across the genome. For the 80cM locus, the average powers of the 20, 30 and 40 cM bin widths at λs = 1.15 were 0.82, 0.85 and 0.68 respectively. The same pattern was observed at λs = 1.3, as well as for the 10cM locus. The results imply that bin widths of 20 and 30cM have similar power to detect linkage, but larger bins may be less effective when the disease locus is not telomeric.