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.