Several methods may be found for selecting a subset of regressors from a set of k candidate variables in multiple linear regression.
        One possibility is to evaluate all possible regression models and comparing them using Mallows's Cp statistic (Cp) according to Gilmour original study.
        Full model is calculated, all possible combinations of regressors are generated, adjusted Cp for each submodel are computed, and the submodel with the minimum adjusted value Cp (ModelMin) is calculated.
        To identify the final model, the package applies a sequence of hypothesis tests on submodels nested within ModelMin, following the approach outlined in Gilmour's original paper.
        For more details see the help of the function final_model() and the original study (1996) <doi:10.2307/2348411>.

Implements the generalized integration model, which integrates individual-level data and summary statistics under a generalized linear model framework. It supports continuous and binary outcomes to be modeled by the linear and logistic regression models. For binary outcome, data can be sampled in prospective cohort studies or case-control studies. Described in Zhang et al. (2020)<doi:10.1093/biomet/asaa014>.

Helps find meaningful patterns in complex genetic experiments. First gimap takes data from paired CRISPR (Clustered regularly interspaced short palindromic repeats) screens that has been pre-processed to counts table of paired gRNA (guide Ribonucleic Acid) reads. The input data will have cell counts for how well cells grow (or don't grow) when different genes or pairs of genes are disabled. The output of the 'gimap' package is genetic interaction scores which are  the distance between the observed CRISPR score and the expected CRISPR score. The expected CRISPR scores are what we expect for the CRISPR values to be for two unrelated genes. The further away an observed CRISPR score is from its expected score the more we suspect genetic interaction. The work in this package is based off of original research from the Alice Berger lab at Fred Hutchinson Cancer Center (2021) <doi:10.1016/j.celrep.2021.109597>.