plot_multiple_branches_pseudotime: Create a kinetic curves to demonstrate the bifurcation of...

In monocle: Clustering, differential expression, and trajectory analysis for single- cell RNA-Seq

Description

Create a kinetic curves to demonstrate the bifurcation of gene expression along multiple branches

Usage

plot_multiple_branches_pseudotime(cds, branches, branches_name = NULL,
  min_expr = NULL, cell_size = 0.75, norm_method = c("vstExprs", "log"),
  nrow = NULL, ncol = 1, panel_order = NULL, color_by = "Branch",
  trend_formula = "~sm.ns(Pseudotime, df=3)", label_by_short_name = TRUE,
  TPM = FALSE, cores = 1)

Arguments

cds	CellDataSet for the experiment (normally only the branching genes detected with BEAM)
branches	The terminal branches (states) on the developmental tree you want to investigate.
branches_name	Name (for example, cell type) of branches you believe the cells on the branches are associated with.
min_expr	The minimum level of expression to show in the plot
cell_size	A number how large the cells should be in the plot
norm_method	Determines how to transform expression values prior to rendering
nrow	the number of rows used when laying out the panels for each gene's expression
ncol	the number of columns used when laying out the panels for each gene's expression
panel_order	the order in which genes should be layed out (left-to-right, top-to-bottom)
color_by	the cell attribute (e.g. the column of pData(cds)) to be used to color each cell
trend_formula	the model formula to be used for fitting the expression trend over pseudotime
label_by_short_name	label figure panels by gene_short_name (TRUE) or feature id (FALSE)
TPM	Whether to convert the expression value into TPM values.
cores	Number of cores to use when smoothing the expression curves shown in the heatmap.

Value

a ggplot2 plot object

monocle documentation built on Nov. 8, 2020, 5:06 p.m.