ElbowPlot with modifications — ElbowPlot

Creates ElbowPlot with ability to calculate and plot cutoffs for amount of variance conferred by the PCs. Cutoff 1 is PC where principal components only contribute less than 5% of standard deviation and the principal components cumulatively contribute 90% of the standard deviation. Cutoff 2 is point where the percent change in variation between the consecutive PCs is less than 0.1%.

ElbowPlot_scCustom(
  seurat_object,
  ndims = NULL,
  reduction = "pca",
  plot_type = "stdev",
  calc_cutoffs = TRUE,
  plot_cutoffs = TRUE,
  line_colors = c("dodgerblue", "firebrick"),
  cutoff_linewidth = NULL,
  linewidth = deprecated()
)

Arguments

seurat_object: name of Seurat object
ndims: The number of dims to plot. Default is NULL and will plot all dims
reduction: The reduction to use, default is "pca"
plot_type: One of "stdev" (default), "variance" (per-PC \ "cumulative_variance" (running sum of those percentages; equals 100\ stored PC when ndims spans all of them)
calc_cutoffs: logical, whether or not to calculate the cutoffs, default is TRUE.
plot_cutoffs: logical, whether to plot the cutoffs as vertical lines on plot, default is TRUE.
line_colors: colors for the cutoff lines, default is c("dodgerblue", "firebrick").
cutoff_linewidth: width of the cutoff lines, default is NULL, uses ggplot2 default.
linewidth: . See cutoff_linewidth.

Value

ggplot2 object

References

Modified from following: https://hbctraining.github.io/scRNA-seq/lessons/elbow_plot_metric.html.

Examples

library(Seurat)
ElbowPlot_scCustom(seurat_object = pbmc_small)