Haplotypes have gained increasing attention in the mapping of complex-disease genes, because of the abundance of single-nucleotide polymorphisms (SNPs) and the limited power of conventional single-locus analyses. It has been shown that haplotype-inference methods such as Clark's algorithm, the expectation-maximization algorithm, and a coalescence-based iterative-sampling algorithm are fairly effective and economical alternatives to molecular-haplotyping methods. To contend with some weaknesses of the existing algorithms, we propose a new Monte Carlo approach. In particular, we first partition the whole haplotype into smaller segments. Then, we use the Gibbs sampler both to construct the partial haplotypes of each segment and to assemble all the segments together. Our algorithm can accurately and rapidly infer haplotypes for a large number of linked SNPs. By using a wide variety of real and simulated data sets, we demonstrate the advantages of our Bayesian algorithm, and we show that it is robust to the violation of Hardy-Weinberg equilibrium, to the presence of missing data, and to occurrences of recombination hotspots.

Background: Higher fat mass may be an independent risk factor for osteoporosis and osteoporotic fractures. Objective: We aimed to determine the independent contribution of fat mass to osteoporosis and to estimate the risk of osteoporotic fractures in relation to body weight, lean mass, and other confounders. Design: This was a community-based, cross-sectional study of 7137 men, 4585 premenopausal women, and 2248 postmenopausal women aged 25-64 y. Total-body and hip bone mineral content (BMC) and bone mineral density (BMD) and body composition were measured by dual-energy X-ray absorptiometry. Serum lipids were measured. Sex-and menopause-specific multiple generalized linear models were applied. Results: Across 5-kg strata of body weight, fat mass was significantly inversely associated with BMC in the whole body and total hip. When we compared the highest quartile with the lowest quartile of percentage fat mass in men, premenopausal women, and postmenopausal women, the adjusted odds ratios (95% CIs) of osteoporosis defined by hip BMD were 5.2 (2.1, 13.2), 5.0 (1.7, 15.1), and 6.9 (4.3, 11.2), respectively. Significant linear trends existed for higher risks of osteoporosis, osteopenia, and nonspine fractures with higher percentage fat mass. Significant negative relations were found between whole-body BMC and cholesterol, triacylglycerol, LDL, and the ratio of HDL to LDL in all groups. Conclusions: Risks of osteoporosis, osteopenia, and nonspine fractures were significantly higher for subjects with higher percentage body fat independent of body weight, physical activity, and age. Thus, fat mass has a negative effect on bone mass in contrast with the positive effect of weight-bearing itself.Am J Clin Nutr 2006; 83:146 -54.