setFeatures {scmap} | R Documentation |
This method manually sets the features to be used for projection.
setFeatures(object, features = NULL) setFeatures.SingleCellExperiment(object, features) ## S4 method for signature 'SingleCellExperiment' setFeatures(object, features = NULL)
object |
an object of |
features |
a character vector of feature names |
Please note that feature_symbol
column of rowData(object)
must be
present in the input object and should not contain any duplicated feature names.
This column defines feature names used during projection. Feature symbols
in the reference dataset must correpond to the feature symbols
in the projection dataset, otherwise the mapping will not work!
an object of SingleCellExperiment
class with a new column in
rowData(object)
slot which is called scmap_features
. It can be accessed
by using as.data.frame(rowData(object))$scmap_features
.
library(SingleCellExperiment) sce <- SingleCellExperiment(assays = list(normcounts = as.matrix(yan)), colData = ann) # this is needed to calculate dropout rate for feature selection # important: normcounts have the same zeros as raw counts (fpkm) counts(sce) <- normcounts(sce) logcounts(sce) <- log2(normcounts(sce) + 1) # use gene names as feature symbols rowData(sce)$feature_symbol <- rownames(sce) isSpike(sce, 'ERCC') <- grepl('^ERCC-', rownames(sce)) # remove features with duplicated names sce <- sce[!duplicated(rownames(sce)), ] sce <- setFeatures(sce, c('MMP2', 'ZHX3'))