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  \item Brief literature review:   \begin{itemize}  %\item The availability of whole genome and exome sequencing are enabling rapid advances in genomic research.  \item Rare genetic variants can play major roles in influencing complex traits. \cite{Pritchard_2001, Schork_2009}  \item The rare susceptibility variants identified through sequencing have potential to explain some of the 'missing heritability' of complex traits. \cite{Eichler_2010}.  \item However, standard methods to test for association with single genetic variants are underpowered for rare variants unless sample sizes are very large. \cite{Lee_2014}    \item Overview of 3 types of analysis methods (Besides single-variant approach)   \begin{itemize}  \item Pooled-variant methods combine 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 across for  multiple variant sites within variants into  a gene. Pooling information in this way can enrich single genetic score or by evaluating  the association signal 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 \cite{Cho_2010}. This may be a more powerful approach than pooling marginal associations across variants when trait-influencing variants are in low linkage disequilibrium.   \item 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}