Large family studies of complex disorders can be used to detect a genomic region linked with a particular illness. Where multiple families are found with common regions of linkage, this could be due to an ancestral mutation common to these families. In this thesis, I describe a method for studying allele sharing in families that share a linkage region, to identify a common founder mutation, thus maximising the results of replicated linkage studies. The method tests the hypothesis that the evidence for shared linkage is derived from the sharing of a common affected ancestor. By comparing the allelic similarity of haplotypes across common linkage regions, it is possible to identify any regions that are identical by descent between the families. A method of permutation analysis followed by a nested permutation technique have been developed to assess the statistical significance of allele sharing scores. Chapter 3 describes the proof of principle of the method through its application to known cystic fibrosis mutations and through simulated datasets. This provides both a real dataset and a much more diverse range of simulated conditions on which to test the method. The range of simulated data was also used to develop a set of criteria for the effective us of the method. In Chapter 4, the allele sharing method was applied to two replicated linkage regions on chromosome 4p15-16 that segregate with bipolar affective disorder. This was done over two phases, first taking in markers covering the genic regions of the shared linkage region and then followed up with a complete coverage of the region. This analysis identified a 200kb region with significant confidence within the 8Mb of the two linkage regions. The study of this region presents a clear example of how replicated linkage results that are caused by some founder effect, can be examined, and refined using this allele sharing method to vastly reduce the region under investigation.