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\item Overview of 3 types of analysis methods (Besides single-variant approach)   \begin{itemize}  \item Pooled-variant methods evaluate the cumulative effects of multiple genetic variants in a genomic region. The score statistics from marginal models of the trait association with individual variants are collapsed into a single test statistic, either by combining the information for multiple variants into a single genetic score or by evaluating the distribution of the pooled score statistics of individual variants. \cite{Lee_2014}  \item Joint-modeling methods identify the joint effect of multiple genetic variants simultaneously (e.g., \cite{Cho_2010}). Cho et al. 2010}).  These methods can assess whether a variant carries any further information about the trait beyond what is explained by the other variants. When trait-influencing variants are in low linkage disequilibrium, this approach may be more powerful than pooling test statistics for marginal associations across variants. \item Individuals Tree-based methods assess whether trait values co-cluster with the ancestral tree for the haplotypes (e.g. Bardel et al. 2005).Individuals  carrying the same disease-predisposing variant are likely to inherit it from the same ancestor. Therefore, cases will tend to cluster together in the underlying genealogy. A method to detect clustering of the cases on the tree represents an alternative grouping method based on relatedness \cite{Burkett_2013}. \end{itemize}    \end{itemize}