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\end{itemize}  \item C-alpha \cite{Neale_2011}: %Test the variance of the effect size for variants in a specific genomic window (No effect, increase or decrease risk).  \item C-alpha test of \cite{Neale_2011} is a variance components approach that assumes the effects of variants are random.   \item C-alpha procedure tests the variance of genetic effects under the assumption that variants observed in cases and controls are a mixture of deleterious, risk,  protective or neutral variants.\begin{itemize}  \item Sensitive to risk and protective variants in the same gene.  \item Powerful \citeNP{Neale_2011} found that C-alpha showed greater power than burden test  when the effects are in different directions. protective and risk variant exist.  \item R package: SKAT\end{itemize}  \end{itemize}    \item Joint-modeling method