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\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., 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 Review ideas in Blossoc for "tree based" methods.    \item  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 ancestral  tree represents an alternative grouping method based on relatedness \cite{Burkett_2013}. \item Review limitation of Burkett et al. study.  \end{itemize}    \end{itemize} 
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%Make the point here in the intro that we've included true trees in the comparison, even though we won't know them in practice because in principle this should be the best result.  \begin{itemize}  \item Genealogical tree represents the ancestry of the sample at each locus in the region.  \item Individuals Haplotypes  carrying the same disease risk alleles tend to cluster on a tree at the disease risk locus. \item In practice true trees are unknown. However, cluster statistics based on true trees represent a best case for detection detecting  association as tree uncertainty is eliminated. \item Burkett et al. etablished the optimality of these tree tests for detecting association. We therefore used clustering test tests  based on true trees asa  bench mark. marks for comparison to the popular association methods.  \end{itemize}