plot_genes_in_pseudotime {monocle} | R Documentation |
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
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, 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)