addPrcomp {dittoSeq}

R Documentation

Add a prcomp pca calculation to a SingleCellExperiment object containing bulk or single-cell data

Description

Add a prcomp pca calculation to a SingleCellExperiment object containing bulk or single-cell data

Usage

addPrcomp(object, prcomp, name = "pca", key = "PC")

Arguments

object	the SingleCellExperiment object.
prcomp	a prcomp output which will be added to the object
name	String name for the reduction slot. Normally, this will be "pca", but you can hold any number of PCA calculations so long as a unique name is given to each. This will become the name of the slot and what should be provided to the reduction.use input when making a dittoDimPlot. When the name given is the same as that of a slot that already exists inside the object, the previous slot is replaced with the newly provided data.
key	String, like "PC", which sets the default axes-label prefix when this reduction is used for making a dittoDimPlot

Value

Outputs an SingleCellExperiment object with an added or replaced pca reduction slot.

Author(s)

Daniel Bunis

See Also

addDimReduction for adding other types of dimensionality reductions

importDittoBulk for initial import of bulk RNAseq data into dittoSeq as a SingleCellExperiment.

dittoDimPlot for visualizing how samples group within added dimensionality reduction spaces

Examples

example("importDittoBulk", echo = FALSE)

# Calculate PCA with prcomp
#   NOTE: This is typically not done with all genes in a dataset.
#   The inclusion of this example code is not an endorsement of a particular
#   method of PCA. Consult yourself, a bioinformatician, or literature for
#   tips on proper techniques.
calc <- prcomp(t(logcounts(myRNA)), center = TRUE, scale = TRUE)

myRNA <- addPrcomp(
    object = myRNA,
    prcomp = calc)

# Now we can visualize conditions metadata on a PCA plot
dittoDimPlot(myRNA, "conditions", reduction.use = "pca", size = 3)

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