Description Usage Arguments Value Examples
Calculates p-values of a log-likelihood of a list of genes to be associated with each cell type. Log-likelihood is based on gene expression values.
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input |
object of SingleCellExperiment class |
genelist |
column name in the colData slot of the object SingleCellExperiment containing the cell classification information |
a 'list' containing calculated gene index
1 2 3 4 5 6 7 8 9 10 11 12 13 | 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)), ]
index <- buildCellIndex(sce)
res <- findCell(index, genelist = c('SOX6', 'SNAI3'))
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