Package index • RaCInG

Main workflows

compute_kernel(): Compute the RaCInG kernel for one or more patients
compute_kernel_features(): Derive communication features from a kernel
calculateDirect(): Calculate direct communication features from a kernel
calculateWedges(): Calculate wedge features from a kernel
computeTriangles(): Compute triangle features from kernel matrices
computeGSCC(): Compute GSCC features from kernel matrices
countWedges(): Count wedges across Monte Carlo graph simulations
countTrustTriangles(): Count trust triangles across Monte Carlo graph simulations
countCycleTriangles(): Count cycle triangles across Monte Carlo graph simulations
countDirect(): Count direct edges across Monte Carlo graph simulations
countGSCC(): Count GSCC contributions across Monte Carlo graph simulations
model1(): Generate a single RaCInG graph realization
runSim(): Run Monte Carlo simulations for one or more patients
getGSCCAnalytically(): Legacy GSCC helper

createCellLigList(): Read a cell-to-ligand compatibility matrix
createCellRecList(): Read a cell-to-receptor compatibility matrix
createCellTypeDistr(): Read and normalize cell-type abundance estimates
createInteractionDistr(): Read ligand-receptor interaction probabilities
Read_Lig_Rec_Interaction(): Read a ligand-receptor sign matrix
genRandomCellTypeDistr(): Generate a random cell-type distribution
genRandomLigRecDistr(): Generate a random ligand-receptor distribution
genRandomCellLigands(): Generate a random cell-to-ligand compatibility matrix
genRandomCellReceptors(): Generate a random cell-to-receptor compatibility matrix
genRandomCellTypeList(): Sample cell-type labels for graph vertices
generateUniformLRGraph(): Generate a graph under a uniformized ligand-receptor baseline

EdgetoAdj(): Convert an edge list to a sparse adjacency matrix
EdgetoAdj_No_loop(): Convert an edge list to a sparse adjacency matrix without self-loops
Count_Types(): Count graph motifs by cell-type combination
Trust_Triangles(): Enumerate outward trust triangles
Cycle_Triangles(): Enumerate directed cycle triangles
Wedges(): Enumerate wedges in a directed graph
Find_Number_Trust_Triangles_Unique(): Count unique trust triangles in a directed graph
Find_Number_Triangles(): Count triangles allowing multi-edges
Find_Number_Triangles_Unique(): Count unique triangles in a directed graph
Find_Number_2Loops(): Count reciprocal 2-loops allowing multi-edges
Find_Number_2Loops_Unique(): Count unique reciprocal 2-loops
Find_Number_Wedges(): Count wedges allowing multi-edges
Find_Number_Wedges_Unique(): Count unique wedges in a directed graph
GSCC(): Extract the giant strongly connected component
IN(): Compute the IN component of a directed graph
OUT(): Compute the OUT component of a directed graph

wilcox_group_test(): Run Wilcoxon tests across network features
volcano_plot(): Create a volcano plot from Wilcoxon results
Read_Sim_Output(): Read a RaCInG simulation output file
compute_results_processing(): Convert raw simulation outputs into feature matrices