plot_genes_in_pseudotime {monocle} | R Documentation

## Plots expression for one or more genes as a function of pseudotime

### Description

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

### Usage

    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
    )

### Arguments

`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.

### Value

a ggplot2 plot object

### Examples

    ## 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)

[Package monocle version 2.22.0 Index]