plotSmoothFit: Gene Smooth: Plot a single fit
In farrellja/URD: URD

Description Usage Arguments Value Examples

This plots gene expression in groups of cells and a curve representing its mean expression (generated using a smoothing algorithm). It takes output from either geneSmoothFit or geneCascadeProcess. (Output from geneCascadeProcess may also be plotted with geneCascadeImpulsePlots.) If multiple genes are provided, they are plotted on the same plot in different colors if multiplot=F or as a grid of plots per gene if multiplot=T.

plotSmoothFit(
  smoothed.fit,
  genes,
  scaled = T,
  multiplot = F,
  plot.data = T,
  alpha.data = 0.2,
  alpha.smooth = 1,
  lwd.smooth = 1,
  plot.title = NULL
)

`smoothed.fit`	(List) Output from either `geneSmoothFit` or `geneCascadeProcess`
`genes`	(Character vector) Genes to include in the plot
`scaled`	(Logical) Plot actual expression values (`FALSE`) or expression scaled to its maximum value (`TRUE`)
`multiplot`	(Logical) If multiple genes are provided, they are plotted on the same plot in different colors if `multiplot=F` or as a grid of plots per gene if `multiplot=T`
`plot.data`	(Logical) Plot data points?
`alpha.data`	(Numeric: 0-1) Transparency of data points
`alpha.smooth`	(Numeric: 0-1) Transparency of curve
`lwd.smooth`	(Numeric) Line width of curve
`plot.title`	(Character) Title of plot (Default `NULL` is no title)

A ggplot2 object

# Calculate spline fit
expressed.spline <- geneSmoothFit(hydra.spumous, method = "spline", 
  pseudotime = "pseudotime", cells = colnames(hydra.spumous@logupx.data),
  genes = expressed.genes, moving.window = 1, cells.per.window = 5, 
  spar = 0.875
)
# Plot a few genes on the fit curves
genes.spline.plot <- c("t14194aep|WNT3_MOUSE", "t15597aep|WNT1_DANRE",
  "t20768aep|BRAC_CANLF", "t29725aep|BRAC_CHICK", "t22116aep|ETV1_MOUSE"
)
plotSmoothFit(expressed.spline, genes = genes.spline.plot, scaled = T)