||The purpose of this dissertation is to evaluate, modify, and develop bioinformatic tools that can be applied to extended pedigrees for the localization of genes involved in complex diseases, specifically focusing on Tourette Syndrome (TS) and Autism Spectrum Disorder (ASD). Three analytically techniques are examined - linkage, association, and shared genomic segments (SGS). With respect to linkage, MCMC methods were applied to a large TS pedigree to conduct a parametric linkage analysis. This was the first time that a linkage analysis was performed on the full pedigree in its entirety. We found linkage peaks for a qualitative analysis of TS on chromosome 3p and for a quantitative analysis of tic severity on chromosome 1p (LOD = 3.1 and 3.3, respectively). With respect to association, we developed a new weighting algorithm to perform association analyses in pedigrees. The algorithm considers all relationships simultaneously in arbitrary-structured pedigrees and assigns weights to pedigree members that can be used in subsequent association analyses to address relatedness. This new method outperformed a previous weighting approach. However, limitations were also evident. Further examination of the validity and power of this weighting approach, in addition to other association analyses, variance correction (VC) and a naïve (ignore relatedness), was performed.