plot_pc_variance_explained {monocle} | R Documentation |
Plots the percentage of variance explained by the each component based on PCA from the normalized expression data using the same procedure used in reduceDimension function.
plot_pc_variance_explained( cds, max_components = 100, norm_method = c("log", "vstExprs", "none"), residualModelFormulaStr = NULL, pseudo_expr = NULL, return_all = F, use_existing_pc_variance = FALSE, verbose = FALSE, ... )
cds |
CellDataSet for the experiment after running reduceDimension with reduction_method as tSNE |
max_components |
Maximum number of components shown in the scree plot (variance explained by each component) |
norm_method |
Determines how to transform expression values prior to reducing dimensionality |
residualModelFormulaStr |
A model formula specifying the effects to subtract from the data before clustering. |
pseudo_expr |
amount to increase expression values before dimensionality reduction |
return_all |
A logical argument to determine whether or not the variance of each component is returned |
use_existing_pc_variance |
Whether to plot existing results for variance explained by each PC |
verbose |
Whether to emit verbose output during dimensionality reduction |
... |
additional arguments to pass to the dimensionality reduction function |
## Not run: library(HSMMSingleCell) HSMM <- load_HSMM() plot_pc_variance_explained(HSMM) ## End(Not run)