Eng                     Spatial transcriptomics data of mouse
                        fibroblast cells
NegHyper                Negative hypergeometric distribution (taken
                        from orphaned extraDistr package)
Yang                    Spatial transcriptomics data of Selaginella
                        moellendorffii roots
addCell                 Add cell boundaries and event-wise cell
                        identifiers to a hyperframe.
addDesign               Add design variables to hyperframe
addNuclei               Add nuclei to a hyperframe
addTabObs               Add tables with gene counts to the hyperframe,
                        presort by gene and x-ccordinate and add design
                        varibales
buildDataFrame          Extract a data frame for a certain gene and PI
                        from a fitted object
buildFormula            Build a formula from different components
buildHyperFrame         Build a hyperframe containing all point
                        patterns of an experiment.
calcIndividualPIs       Calculate individual PI entries of a single
                        point pattern
calcNNPI                Estimate the PI for nearest neighbour distances
                        with the negative hypergeometric distribution
calcWindowDistPI        Estimate the PI for the distance to a fixed
                        object of interest, such as a cell wall or
                        centroid
centerNumeric           Center numeric variables
checkFeatures           Check if features are present in hyperframe
checkPi                 Check if the required PI's are present in the
                        object
constructDesignVars     Check for or construct design matrix
convertToOwins          Convert windows to spatstat.geom owin format
crossdistWrapper        A wrapper for C-functions calculating
                        cross-distance matrix fast
estGradients            Estimate gradients over multiple point
                        patterns, and test for significance
estPis                  Estimate probabilistic indices and add a
                        variance weighting function.
evalWeightFunction      Evaluate a variance weighting function
extractResults          Extract results from a list of fitted LMMs. For
                        internal use mainly.
findEcdfsCell           Construct empirical cumulative distribution
                        functions (ecdfs) for within-cell distances
findOverlap             Find overlap between list of windows
fitGradient             Test for presence of gradient in a hyperframe
                        of point patterns
fitLMMs                 Fit linear (mixed) models for all probabilistic
                        indices (PIs) and all genes
fitPiModel              Fit a linear model for an individual gene and
                        PI combination
fitSingleLmmModel       Take an existing frame, add outcome and weight
                        and fit lmer model
getCoordsMat            Extract coordinates from a point pattern or
                        data frame
getDesignVars           Extract design variables from a hyperframe
getElement              Extract en element from a matrix or vector
getFeatures             Extract all unique and estimated features from
                        an object
getGp                   Get a gene pair from a vector or list
getHypFrame             Extract the hyperframe
getPiAndWeights         Build a matrix with pi and weights
lm_from_wfit            Add compoments to a result from lm.wfit to make
                        it a minimally valid lm object
loadBalanceBplapply     Parallel processing with BiocParallel with load
                        balancing
makeDesignVar           Make design variable by combining different
                        design variables
makePairs               An aux function to build gene pairs
named.contr.sum         A version of contr.sum that retains names, a
                        bit controversial but also clearer
nestRandom              Nest random effects within fixed variables, in
                        case the names are the same
plotCells               Plot the n cells with highest abundance of a
                        feature
plotExplore             Plot a hyperframe with chosen features
                        highlighted
plotTopResults          Plot the most significant findings for a
                        certain PI
plotWf                  Plot the variance weighting function
selfName                Name a character vector after itself
sortGp                  Sort feature pairs alphabetically
splitWindow             Split a number of plots into rows and columns
subSampleP              Subsample a point pattern when it is too large
sund                    Helper function to spit gene pairs
writeToXlsx             Write effect sizes and p-values results to an
                        excel worksheet
