This package is for subset-based association analysis of heterogeneous but possibly related traits.
The package consists of two main functions: (1) h.traits and (2) h.types. The function h.traits is suitable for conducting meta-analysis of studies of possibly different traits when summary level data are available from individual studies. The function allows correlation among different studies/traits, which, for example, may arise due to shared subjects across studies. The function can also be used to conduct "meta-analysis" across multiple correlated traits on the same individuals by appropriately specifying the correlation matrix for the multivariate trait. The method, however, is not optimized yet (from a power perspective) for analyzing multivariate traits measured on the same individuals. The function h.types is suitable for analysis of case-control studies when cases consist of distinct disease subtypes. This function assumes individual level data are available. The functions h.summary and h.forestPlot are useful for summarizing results and displaying forest plots. The helper functions z.max and p.dlm are generic functions called internally for obtaining the maximized subset-based test-statistics and the corresponding p-values approximated by the Discrete Local Maximization (DLM) method. These functions can be further customized for specific applications. For example, the default options of these functions currently assume all possible subsets to search. For analysis of case-control studies with ordered diseased subtypes (e.g. stages of a cancer), however, it may be more meaningful to restrict the subset search to incorporate ordering constraints among the disease subtypes. In such a situation, one can pass a function argument sub.def to z.max and p.dlm for performing restricted subset searches.
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