data_transform_quantile {peco} | R Documentation |
For each gene, transform counts to CPM and then to a normal distribution.
data_transform_quantile(sce, ncores = 2)
sce |
SingleCellExperiment Object. |
ncores |
We use doParallel package for parallel computing. |
SingleCellExperiment Object with an added slot of cpm_quant, cpm slot is added if it doesn't exist.
Joyce Hsiao
# use our data library(SingleCellExperiment) data(sce_top101genes) # perform CPM normalization using scater, and # quantile-normalize the CPM values of each gene to normal distribution sce_top101genes <- data_transform_quantile(sce_top101genes, ncores=2) plot(y=assay(sce_top101genes, "cpm_quantNormed")[1,], x=assay(sce_top101genes, "cpm")[1,], xlab = "CPM bbefore quantile-normalization", ylab = "CPM after quantile-normalization")