plot_genes_positive_cells {monocle} | R Documentation

## Plots the number of cells expressing one or more genes as a barplot

### Description

@description Accetps a CellDataSet and a parameter,"grouping", used for dividing cells into groups. Returns one or more bar graphs (one graph for each gene in the CellDataSet). Each graph shows the percentage of cells that express a gene in the in the CellDataSet for each sub-group of cells created by "grouping".

Let's say the CellDataSet passed in included genes A, B, and C and the "grouping parameter divided all of the cells into three groups called X, Y, and Z. Then three graphs would be produced called A, B, and C. In the A graph there would be three bars one for X, one for Y, and one for Z. So X bar in the A graph would show the percentage of cells in the X group that express gene A.

### Usage

    plot_genes_positive_cells(cds_subset, grouping = "State", min_expr = 0.1,
      nrow = NULL, ncol = 1, panel_order = NULL, plot_as_fraction = TRUE,
      label_by_short_name = TRUE, relative_expr = TRUE, plot_limits = c(0,
      100))

### Arguments

`cds_subset` | CellDataSet for the experiment
`grouping` | the cell attribute (e.g. the column of pData(cds)) to group cells by on the horizontal axis
`min_expr` | the minimum (untransformed) expression level to use in plotted the genes.
`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)
`plot_as_fraction` | whether to show the percent instead of the number of cells expressing each gene
`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
`plot_limits` | A pair of number specifying the limits of the y axis. If NULL, scale to the range of the data.

### Value

a ggplot2 plot object

### Examples

    ## Not run:
    library(HSMMSingleCell)
    HSMM <- load_HSMM()
    MYOG_ID1 <- HSMM[row.names(subset(fData(HSMM), gene_short_name %in% c("MYOG", "ID1"))),]
    plot_genes_positive_cells(MYOG_ID1, grouping="Media", ncol=2)

    ## End(Not run)

[Package monocle version 2.18.0 Index]