addDimReduction: Add any dimensionality reduction space to a...

In dtm2451/dittoSeq: User Friendly Single-Cell and Bulk RNA Sequencing Visualization

Add any dimensionality reduction space to a SingleCellExperiment object containing bulk or single-cell data

Description

Add any dimensionality reduction space to a SingleCellExperiment object containing bulk or single-cell data

Usage

addDimReduction(object, embeddings, name, key = .gen_key(name))

Arguments

object	the bulk or single-cell SingleCellExperiment object to add the dimensionality reduction to. (dittoSeq utilizes the SingleCellExperiment object even for bulk data because it provides a convenient slots for all data that dittoSeq requires)
embeddings	a numeric matrix or matrix-like object, with number of rows equal to ncol(object), containing the coordinates of all cells / samples within the dimensionality reduction space.
name	String name for the reduction slot. Example: "pca". 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. If nothing is provided, a key will be automatically generated.

Value

Outputs a SingleCellExperiment object with an added or replaced dimensionality reduction slot.

Author(s)

Daniel Bunis

See Also

addPrcomp for a prcomp specific PCA import wrapper

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
#   NOTE: This is typically not done with all genes in the 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.
embeds <- prcomp(t(logcounts(myRNA)), center = TRUE, scale = TRUE)$x

myRNA <- addDimReduction(
    object = myRNA,
    embeddings = embeds,
    name = "pca",
    key = "PC")

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

dtm2451/dittoSeq documentation built on May 5, 2024, 11:19 a.m.