BuildDataAndLines       A helper function for the PlotPair functions
                        (i.e. the highcharter one and the flat, base-R
                        one).
CreateCrossValFolds     Creates multiple cross-validation folds from
                        the data. Format is a list of IntLIMData
                        training and testing pairs. The "training" slot
                        contains all data except that in the given
                        fold, and the "testing" contains all data in
                        the fold.
DistPvalues             Visualize the distribution of unadjusted
                        p-values from linear models
DistRSquared            Visualize the distribution of unadjusted
                        p-values from linear models
FilterData              Filter input data by abundance values and
                        number of missing values.
FilterDataFolds         Filter input data by abundance values (analyte
                        data) and number of missing values.
HistogramPairs          histogram of analyte pairs depending upon
                        independent or outcome analyte
IntLimData-class        IntLimData class
IntLimResults-class     IntLimResults class
InteractionCoefficientGraph
                        Graphs a scatterplot of pairs vs. the
                        interaction coefficient for the pair
MarginalEffectsGraph    Creates a dataframe of the marginal effect of
                        phenotype
MarginalEffectsGraphDataframe
                        Creates a dataframe of the marginal effect of
                        phenotype
OutputData              Output data into individual CSV files.  All
                        data will be zipped into one file with all
                        data.
OutputResults           Output results into a zipped CSV file.  Results
                        include gene and metabolite pairs, along with
                        model interaction p-values, and correlations in
                        each group being evaluated.
PValueBoxPlots          Visualize the distribution of unadjusted
                        p-values for all covariates from linear models
                        using a bar chart.
PermutationCountSummary
                        Return the number of significant analytes and
                        the number of permutations in which each
                        analyte is significant. If plot = TRUE, show a
                        box plot of number of significant analytes over
                        permutations, overlaid with the number of
                        significant analytes in the original data.
PermutationPairSummary
                        Return the number of significant analytes /
                        pairs per permutation and the number of
                        permutations in which each analyte is
                        significant. If plot = TRUE, show a box plot of
                        number of significant analytes over
                        permutations, overlaid with the number of
                        significant analytes in the original data.
PermuteIntLIM           Run permutations of the IntLIM code to search
                        for random cross-omic associations in dataset
PlotDistributions       Get some stats after reading in data
PlotFoldOverlapUpSet    Makes an UpSet plot showing the filtered pairs
                        of analytes found in each fold. This plot
                        should only be made for cross-validation data.
PlotPCA                 PCA plots of data for QC
PlotPair                scatter plot of pairs (based on user selection)
PlotPairFlat            scatter plot of pairs (based on user
                        selection). This version does not use
                        highcharter and instead plots a base R plot.
ProcessResults          Retrieve significant pairs, based on adjusted
                        p-values. For each pair that is statistically
                        significant, calculate the correlation within
                        group1 (e.g. cancer) and the correlation within
                        group2 (e.g. non-cancer).  Users can then
                        remove pairs with a difference in correlations
                        between groups 1 and 2 less than a user-defined
                        threshold.
ProcessResultsAllFolds
                        Retrieve significant pairs, based on adjusted
                        p-values, interaction coefficient percentile,
                        and r-squared values. This is a wrapper for
                        ProcessResults.
ProcessResultsContinuous
                        Retrieve significant pairs (aka filter out
                        nonsignificant pairs) based on value of
                        analyte:type interaction coefficient from
                        linear model
ReadData                Read in CSV file
RemovePlusInCovars      RemovePlusInCovars
RunCrossValidation      Runs the cross-validation end-to-end using the
                        following steps: 1. Create multiple
                        cross-validation folds from the data. 2. Filter
                        each fold using the filtering criteria applied
                        to the entire dataset. 3. Run IntLIM for all
                        folds. 4. Process the results for all folds.
RunIntLim               Run linear models and retrieve relevant
                        statistics
RunIntLimAllFolds       Run linear models for all data folds. This is a
                        wrapper to RunIntLim.
RunLM                   Function that runs linear models and returns
                        interaction p-values.
ShowStats               Get some stats after reading in data
getQuantileForInteractionCoefficient
                        Function that gets numeric cutoffs from
                        percentile
getStatsAllLM           Function that runs Linear Models for all
                        analytes
getstatsOneLM           Function that runs linear models for analyte
                        vs. all analytes of the other type
multi.which             A which for multidimensional arrays. Mark van
                        der Loo 16.09.2011
pvalCoefVolcano         'volcano' plot (difference in correlations vs
                        p-values) of all pairs
runIntLIMApp            run shiny app
