| showProbPlot {digitalDLSorteR} | R Documentation |
Show distribution plots of the cell proportions generated by
generateBulkCellMatrix
Description
Show distribution plots of the cell proportions generated by
generateBulkCellMatrix. These frequencies will determine the
proportion of different cell types used during the simulation of pseudo-bulk
RNA-Seq samples. There are 6 subsets of proportions generated by different
approaches that can be visualized in three ways: box plots, violin plots and
lines plots. You can also plot the probabilities based on the number of
different cell types present in the samples by setting type.plot =
'nCellTypes'.
Usage
showProbPlot(object, type.data, set, type.plot = "boxplot")
Arguments
object |
|
type.data |
Subset of data to show: |
set |
Integer determining which of the 6 different subsets to display. |
type.plot |
Character determining which type of visualization to
display. It can be |
Details
These plots are only for diagnostic purposes. This is the reason because they are generated without any parameter introduced by the user.
Value
A ggplot object.
See Also
Examples
# simulating data
set.seed(123) # reproducibility
sce <- SingleCellExperiment::SingleCellExperiment(
assays = list(
counts = matrix(
rpois(100, lambda = 5), nrow = 40, ncol = 30,
dimnames = list(paste0("Gene", seq(40)), paste0("RHC", seq(30)))
)
),
colData = data.frame(
Cell_ID = paste0("RHC", seq(30)),
Cell_Type = sample(x = paste0("CellType", seq(4)), size = 30,
replace = TRUE)
),
rowData = data.frame(
Gene_ID = paste0("Gene", seq(40))
)
)
DDLS <- createDDLSobject(
sc.data = sce,
sc.cell.ID.column = "Cell_ID",
sc.gene.ID.column = "Gene_ID",
sc.filt.genes.cluster = FALSE,
sc.log.FC = FALSE
)
probMatrix <- data.frame(
Cell_Type = paste0("CellType", seq(4)),
from = c(1, 1, 1, 30),
to = c(15, 15, 50, 70)
)
DDLS <- generateBulkCellMatrix(
object = DDLS,
cell.ID.column = "Cell_ID",
cell.type.column = "Cell_Type",
prob.design = probMatrix,
num.bulk.samples = 60
)
lapply(
X = 1:6, FUN = function(x) {
showProbPlot(
DDLS,
type.data = "train",
set = x,
type.plot = "boxplot"
)
}
)