plot_genes_positive_cells: Plots the number of cells expressing one or more genes as a...

In cole-trapnell-lab/monocle-release: Clustering, differential expression, and trajectory analysis for single- cell RNA-Seq

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)

cole-trapnell-lab/monocle-release documentation built on May 13, 2019, 8:50 p.m.