my_plot_genes_in_pseudotime: Plots expression for one or more genes as a function of...
In efheuston/MyPlotTrajectoryPackage:

Description Usage Arguments Value Examples

Plots expression for one or more genes as a function of pseudotime. Plotting allows you determine if the ordering produced by orderCells() is correct and it does not need to be flipped using the "reverse" flag in orderCells

my_plot_genes_in_pseudotime(cds_subset, min_expr = NULL, cell_size = 0.75,
  nrow = NULL, ncol = 1, panel_order = NULL, color_by = "State",
  trend_formula = "~ sm.ns(Pseudotime, df=3)", label_by_short_name = TRUE,
  relative_expr = TRUE, point_colors = c("#cb4bbe", "lightskyblue",
  "grey37", "#53ba48", "moccasin", "#dcca44", "#502d70", "#afd671", "#cb4471",
  "#69da99", "#d44732", "#6fd3cf", "#5d2539", "#cfd0a0", "blue", "#d2883b",
  "#6793c0", "#898938", "#c98ac2", "yellow", "#c4c0cc", "#7d3d23", "#00a5ff",
  "#d68d7a", "#a2c1a3"), vertical_jitter = NULL, horizontal_jitter = NULL)

`cds_subset`	CellDataSet for the experiment
`min_expr`	the minimum (untransformed) expression level to use in plotted the genes.
`cell_size`	the size (in points) of each cell used in the plot
`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)
`relative_expr`	Whether to transform expression into relative values
`vertical_jitter`	A value passed to ggplot to jitter the points in the vertical dimension. Prevents overplotting, and is particularly helpful for rounded transcript count data.
`horizontal_jitter`	A value passed to ggplot to jitter the points in the horizontal dimension. Prevents overplotting, and is particularly helpful for rounded transcript count data.

a ggplot2 plot object

## Not run: 
library(HSMMSingleCell)
HSMM <- load_HSMM()
my_genes <- row.names(subset(fData(HSMM), gene_short_name %in% c("CDK1", "MEF2C", "MYH3")))
cds_subset <- HSMM[my_genes,]
plot_genes_in_pseudotime(cds_subset, color_by="Time")

## End(Not run)