scmapCluster {scmap} | R Documentation |
Projection of one dataset to another
scmapCluster(projection = NULL, index_list = NULL, threshold = 0.7) scmapCluster.SingleCellExperiment(projection, index_list, threshold) ## S4 method for signature 'SingleCellExperiment' scmapCluster(projection = NULL, index_list = NULL, threshold = 0.7)
projection |
'SingleCellExperiment' object to project |
index_list |
list of index objects each coming from the output of 'indexCluster' |
threshold |
threshold on similarity (or probability for SVM and RF) |
The projection object of SingleCellExperiment
class with labels calculated by 'scmap' and stored in
the scmap_labels
column of the rowData(object)
slot.
library(SingleCellExperiment) sce <- SingleCellExperiment(assays = list(normcounts = as.matrix(yan)), colData = ann) # this is needed to calculate dropout rate for feature selection # important: normcounts have the same zeros as raw counts (fpkm) counts(sce) <- normcounts(sce) logcounts(sce) <- log2(normcounts(sce) + 1) # use gene names as feature symbols rowData(sce)$feature_symbol <- rownames(sce) # remove features with duplicated names sce <- sce[!duplicated(rownames(sce)), ] sce <- selectFeatures(sce) sce <- indexCluster(sce) sce <- scmapCluster(sce, list(metadata(sce)$scmap_cluster_index))