Phemd-methods {phemd} | R Documentation |
Setter function for protein / gene markers
Setter function for stored expression data
Setter function for single-cell expression data aggregated from multiple samples
Setter function for indices of cells subsampled from each sample during aggregation
Setter function for boolean denoting whether cells were subsampled from each sample during aggregation
Setter function for Monocle2 CellDataSet object for experiment
Setter function for Seurat object for experiment
Setter function for cell subtype frequencies of each single-cell sample
Setter function for batch IDs of each single-cell sample
Setter function for EMD ground distance matrix
selectMarkers(obj) <- value ## S4 replacement method for signature 'Phemd' selectMarkers(obj) <- value rawExpn(obj) <- value ## S4 replacement method for signature 'Phemd' rawExpn(obj) <- value pooledCells(obj) <- value ## S4 replacement method for signature 'Phemd' pooledCells(obj) <- value subsampledIdx(obj) <- value ## S4 replacement method for signature 'Phemd' subsampledIdx(obj) <- value subsampledBool(obj) <- value ## S4 replacement method for signature 'Phemd' subsampledBool(obj) <- value monocleInfo(obj) <- value ## S4 replacement method for signature 'Phemd' monocleInfo(obj) <- value seuratInfo(obj) <- value ## S4 replacement method for signature 'Phemd' seuratInfo(obj) <- value celltypeFreqs(obj) <- value ## S4 replacement method for signature 'Phemd' celltypeFreqs(obj) <- value batchIDs(obj) <- value ## S4 replacement method for signature 'Phemd' batchIDs(obj) <- value GDM(obj) <- value ## S4 replacement method for signature 'Phemd' GDM(obj) <- value
obj |
A Phemd object |
value |
Assignment object |
Updated Phemd object
Updated Phemd object
Updated Phemd object
Updated Phemd object
Updated Phemd object
Updated Phemd object containing Seurat object
Updated Phemd object
Updated Phemd object
Updated Phemd object
phemdObj <- createDataObj(all_expn_data, all_genes, as.character(snames_data)) new_genes <- all_genes new_genes[1] <- 'IL2R' selectMarkers(phemdObj) <- new_genes phemdObj <- createDataObj(all_expn_data, all_genes, as.character(snames_data)) new_expn_data <- all_expn_data new_expn_data <- lapply(new_expn_data, function(x) {log2(x+1)}) rawExpn(phemdObj) <- new_expn_data phemdObj <- createDataObj(all_expn_data, all_genes, as.character(snames_data)) aggregated_data <- t(do.call(rbind,all_expn_data)) pooledCells(phemdObj) <- aggregated_data phemdObj <- createDataObj(all_expn_data, all_genes, as.character(snames_data)) subsampledIdxList<- rep(list(1:10), length(all_expn_data)) #subsampled cells 1-10 from each sample subsampledIdx(phemdObj) <- subsampledIdxList phemdObj <- createDataObj(all_expn_data, all_genes, as.character(snames_data)) subsampledBool(phemdObj) <- TRUE phemdObj <- createDataObj(all_expn_data, all_genes, as.character(snames_data)) mydata <- pooledCells(phemdObj) myCellDataSet <- newCellDataSet(mydata,phenoData=NULL, expressionFamily=VGAM::negbinomial.size()) monocleInfo(phemdObj) <- myCellDataSet phemdObj <- createDataObj(all_expn_data, all_genes, as.character(snames_data)) my_seuratObj <- Seurat::CreateSeuratObject(counts = t(all_expn_data[[1]]), project = "A") seuratInfo(phemdObj) <- my_seuratObj phemdObj <- createDataObj(all_expn_data, all_genes, as.character(snames_data)) myCellTypeFreqs <- matrix(rexp(length(all_expn_data)*10, rate=.1), ncol=10) myCellTypeFreqs <- apply(myCellTypeFreqs, 1, function(x) {x / sum(x)}) celltypeFreqs(phemdObj) <- myCellTypeFreqs phemdObj <- createDataObj(all_expn_data, all_genes, as.character(snames_data)) my_seuratObj <- Seurat::CreateSeuratObject(counts = t(all_expn_data[[1]]), project = "A") seuratInfo(phemdObj) <- my_seuratObj batchIDs(phemdObj) <- rep('A', length(all_expn_data)) phemdObj <- createDataObj(all_expn_data, all_genes, as.character(snames_data)) cluster_locs <- 1:10 myGDM <- as.matrix(dist(cluster_locs)) GDM(phemdObj) <- myGDM