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\item A number of methods have been developed to evaluate the disease association for both single-variant and multiple-variants in a genomic region.  \item Besides single-variant methods, we consider three broad classes of methods for analysing sequence data: pooled-variant, joint-modelling and tree-based methods.    \item Overview of 3 types of analysis methods (Besides single-variant approach) method)  \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. 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 \cite{Cho_2010}.