# Analyze Single Molecule Spatial Omics Data Using the Probabilistic Index

## Documentation for package ‘smoppix’ version 1.3.4

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

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
addWeightFunction | Estimate probabilistic indices and add a variance weighting function.
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.
buildHyperFrame-method | 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
Eng | Spatial transcriptomics data of mouse fibroblast cells
EngRois | Spatial transcriptomics data of mouse fibroblast cells
estGradients | Estimate gradients over multiple point patterns, and test for significance
estGradientsSingle | Estimate gradients over multiple point patterns, and test for significance
estPis | Estimate probabilistic indices and add a variance weighting function.
estPisSingle | 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
fitLMMsSingle | 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
getEventVars | Extract design variables from a hyperframe
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
getPPPvars | Extract design variables from a hyperframe
getPvaluesGradient | Estimate gradients over multiple point patterns, and test for significance
getResults | Fit linear (mixed) models for all probabilistic indices (PIs) and all genes
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
NegHyper | Negative hypergeometric distribution (taken from orphaned extraDistr package)
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
pnhyper | Negative hypergeometric distribution (taken from orphaned extraDistr package)
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
Yang | Spatial transcriptomics data of Selaginella moellendorffii roots