Efficient use of siblings in testing for linkage and association

Tests of linkage and association between a disease and either a candidate gene or marker allele can be based on sibships with at least one affected and one unaffected sibling. However, specialized techniques are required to account for within-sibship correlation if some sibships contain more than one affected or more than one unaffected sib. In this paper, we propose Within Sibship Paired Resampling (WSPR), a technique that is designed to test the null hypothesis of no linkage or no association, even when sibships contain variable numbers of sibs. One repeatedly generates data subsets based on randomly sampling one affected and one unaffected sibling from each sibship, and each subset is analyzed individually. Then, evidence is combined by averaging results across these resampled data sets, applying a variance expression that implicitly accounts for the correlation among siblings. While the general WSPR procedure allows for numerous testing strategies, we describe two in detail. Simulation results for scenarios with varying degrees of population stratification demonstrate good power for the WSPR testing methods compared to the sib TDT (S-TDT) and the sibship disequilibrium test (SDT).