plot_clusters: Plots kinetic clusters of genes.

In monocle: Clustering, differential expression, and trajectory analysis for single- cell RNA-Seq

Description

returns a ggplot2 object showing the shapes of the expression patterns followed by a set of pre-selected genes. The topographic lines highlight the distributions of the kinetic patterns relative to overall trend lines.

Usage

plot_clusters(cds, clustering, drawSummary = TRUE, sumFun = mean_cl_boot,
  ncol = NULL, nrow = NULL, row_samples = NULL, callout_ids = NULL)

Arguments

cds	CellDataSet for the experiment
clustering	a clustering object produced by clusterCells
drawSummary	whether to draw the summary line for each cluster
sumFun	whether the function used to generate the summary for each cluster
ncol	number of columns used to layout the faceted cluster panels
nrow	number of columns used to layout the faceted cluster panels
row_samples	how many genes to randomly select from the data
callout_ids	a vector of gene names or gene ids to manually render as part of the plot

Value

a ggplot2 plot object

Examples

## Not run: 
full_model_fits <- fitModel(HSMM_filtered[sample(nrow(fData(HSMM_filtered)), 100),],  
   modelFormulaStr="~VGAM::bs(Pseudotime)")
expression_curve_matrix <- responseMatrix(full_model_fits)
clusters <- clusterGenes(expression_curve_matrix, k=4)
plot_clusters(HSMM_filtered[ordering_genes,], clusters)

## End(Not run)

monocle documentation built on Nov. 8, 2020, 5:06 p.m.