Create a scree plot

Source: R/AllGenerics.R, R/plotScree.R

plotScree generates a scree plot to visualize the eigenvalues. The eigenvalues can be provided either as a part of a TreeSummarizedExperiment object or as a separate vector. This plot illustrates the decline in eigenvalues across components, helping to assess the importance of each component.

plotScree(x, ...)

# S4 method for class 'SingleCellExperiment'
plotScree(x, dimred, ...)

# S4 method for class 'ANY'
plotScree(x, ...)

Arguments

x

a TreeSummarizedExperiment eigenvals or a vector.

...

additional parameters for plotting

  • show.barplot: Logical scalar. Whether to show a barplot. (Default: TRUE)

  • show.points: Logical scalar. Whether to show a points. (Default: TRUE)

  • show.line: Logical scalar. Whether to show a line. (Default: TRUE)

  • show.labels: Logical scalar. Whether to show a labels for each point. (Default: FALSE)

  • add.proportion: Logical scalar. Whether to show proportion of explained variance, i.e., raw eigenvalues. (Default: TRUE)

  • add.cumulative: Logical scalar. Whether to show cumulative explained variance calculated from eigenvalues. (Default: FALSE)

  • n: Integer scalar. Number of eigenvalues to plot. If NULL, all eigenvalues are plotted. (Default: NULL)

  • show.names: Logical scalar. Whether to show names of components in x-axis. If FALSE, the index of component is shown instead of names. (Default: FALSE)

  • eig.name: Character scalar. The name of the attribute in reducedDim(x, dimred) that contains the eigenvalues. (Default: c("eig", "varExplained"))

dimred

Character scalar or integer scalar. Determines the reduced dimension to plot. This is used when x is a TreeSummarizedExperiment to extract the eigenvalues from reducedDim(x, dimred).

Value

A ggplot2 object

Details

plotScree generates a scree plot to visualize the relative importance of components in dimensionality reduction techniques such as Principal Component Analysis (PCA) or Principal Coordinate Analysis (PCoA). If the input is a TreeSummarizedExperiment object, the function extracts eigenvalues from the specified reduced dimension slot, which requires that dimensionality reduction has been performed beforehand using a dedicated function. Alternatively, if the input is a vector or an eigenvals object, these values are directly used as eigenvalues for the plot.

The plot can include a combination of barplot, points, connecting lines, and labels, which can be controlled using the show.* parameters.

An option to show cumulative explained variance is also available by setting add.cumulative = TRUE.

Examples


library(miaViz)
library(scater)

data("enterotype", package = "mia")
tse <- enterotype

# Run  PCA and store results into TreeSE
tse <- transformAssay(tse, method = "clr", pseudocount = TRUE)
#> A pseudocount of 5e-09 was applied.
tse <- runPCA(tse, assay.type = "clr")

# Plot scree plot
plotScree(tse, "PCA", add.cumulative = TRUE)