Function reference • scMaSigPro

All functions
`Estimates` `Estimates-class`	Estimates
`MatrixDesign` `MatrixDesign-class`	MatrixDesign
`ParameterConfig` `ParameterConfig-class`	ParameterConfig
`ScMaSigPro` `ScMaSigPro-class`	ScMaSigPro
`Significant` `Significant-class`	Significant
`VariableProfiles` `VariableProfiles-class`	VariableProfiles
`as_scmp()`	Convert 'Cell Dataset' or 'SingleCellExperiment' object to ScMaSigPro object.
`cDense(<ScMaSigPro>)`	Set or get the Dense Column Data of an ScMaSigPro Object
`cDense<-`(<ScMaSigPro>)	Replacement method for cDense
`cDense<-`()	Set the data for Dense Slot
`cDense()`	Get the data for Dense Slot.
`cSparse(<ScMaSigPro>)`	Set or get the Sparse Column Data of an ScMaSigPro Object
`cSparse<-`(<ScMaSigPro>)	Replacement method for cSparse
`cSparse<-`()	Set the data for Sparse Slot
`cSparse()`	Get the data for Sparse Slot.
`create_scmp()`	Create ScMaSigPro Object
`eDense(<ScMaSigPro>)`	Retrieve Expression Data from Dense Slot
`eDense<-`(<ScMaSigPro>,<character>,<matrix>)	Set or Update Expression Data in Dense Slot
`eDense<-`()	Set Expression Counts in Dense Slot
`eDense()`	Retrieve Expression Counts from Dense Slot
`eSparse(<ScMaSigPro>)`	Retrieve Expression Counts from Sparse Slot
`eSparse<-`(<ScMaSigPro>,<character>,<matrix>)	Set Expression Counts in Sparse Slot
`eSparse<-`()	Set Expression Counts in Sparse Slot
`eSparse()`	Get Expression Counts from Sparse Slot
`m3_select_path()`	Select branching paths from a 'Cell Dataset' object from Monocle3
`multi.lin.sce`	Simulated Multifurcating Trajectory SingleCellExperiment Object
`pathAssign(<ScMaSigPro>)`	Set or get the Assignment Matrix.
`pathAssign<-`(<ScMaSigPro>)	Replacement method for pathAssign
`pathAssign<-`()	Replacement method for pathAssign.
`pathAssign()`	Get or set the Branch Assignment Matrix
`pb_counts()`	Create Pseduo-bulk Counts
`plotBinTile()`	Plot Bin Sizes Across Binned Time and Paths
`plotDiagnostics()`	Plot Model Diagnostics
`plotIntersect()`	Generate UpSet Plot
`plotTrend()`	Plot trend of the single gene.
`plotTrendCluster()`	Plot multiple trends of the multiple genes.
`predictors(<ScMaSigPro>)`	Set or get the Predictor Matrix.
`predictors<-`(<ScMaSigPro>)	Replacement method for predictors
`predictors<-`()	Replacement method for predictors.
`predictors()`	Get or set the Predictor Matrix
`queryCoeff()`	Get Features from scMaSigPro Object
`sc.cluster.trend()`	Cluster the counts or coefficients.
`sc.filter()`	Extract significant genes based on R-Square and P-values
`sc.p.vector()`	Perform fitting with full model.
`sc.restruct()`	Restructure the binned data.
`sc.set.poly()`	Set up polynomial models and create Predictor Matrix
`sc.squeeze()`	Pseudo-bulking with optimal number of Pseudotime based bins
`sc.t.fit()`	Perform stepwise regression fit to select for significant terms.
`scmp.ob`	scMaSigPro Object with results
`showCoeff()`	Show or Return the Coefficient matrix
`showGroupCoeff()`	Show or Return the Branching Path Coefficient matrix
`showInflu()`	Return the matrix of genes with influential observation
`showParams()`	Show the parameters used during the workflow.
`showPoly()`	Print the full model formula.
`showSigProf()`	Show or Return the counts for non-flat profile.
`showSol()`	Show or Return the P-values after model fitting.
`showTS()`	Show or Return the t-score matrix
`splat.sim`	Simulated SingleCellExperiment Object

Reference

All functions