cytof_progressionPlot: Progression plot

In cytofkit: cytofkit: an integrated mass cytometry data analysis pipeline

Description

Plot the expression trend along the estimated cell progressing order

Usage

cytof_progressionPlot(data, markers, clusters, orderCol = "isomap_1",
  clusterCol = "cluster", reverseOrder = FALSE, addClusterLabel = TRUE,
  clusterLabelSize = 5, segmentSize = 0.5, min_expr = NULL,
  trend_formula = "expression ~ sm.ns(Pseudotime, df=3)")

Arguments

data	The data frame for progression plot.
markers	The column names of the selected markers for visualization.
clusters	Select clusters for plotting, default selects all.
orderCol	The column name of the estimated cell progression order.
clusterCol	The column name of the cluster results.
reverseOrder	If TRUE, reverse the value of orderCol.
addClusterLabel	If TRUE, add the cluster label on the plot.
clusterLabelSize	Size of the cluster label.
segmentSize	Size of the cluster label arrow.
min_expr	The threshold of the minimal expression value for markers.
trend_formula	A symbolic description of the model to be fit.

Value

A ggplot2 object

Examples

m1 <- c(rnorm(300, 10, 2), rnorm(400, 4, 2), rnorm(300, 7))
m2 <- c(rnorm(300, 4), rnorm(400, 16), rnorm(300, 10, 3))
m3 <- c(rnorm(300, 16), rnorm(400, 40, 3), rnorm(300, 10))
m4 <- c(rnorm(300, 7, 3), rnorm(400, 30, 2), rnorm(300, 10))
m5 <- c(rnorm(300, 27), rnorm(400, 40, 1),rnorm(300, 10))
c <- c(rep(1,300), rep(2,400), rep(3,300))
rnames <- paste(paste('sample_', c('A','B','C','D'), sep = ''), 
rep(1:250,each = 4), sep='_') 
exprs_cluster <- data.frame(cluster = c, m1 = m1, m2 = m2, m3 = m3, m4 = m4, isomap_1 = m5)
row.names(exprs_cluster) <- sample(rnames, 1000)
cytof_progressionPlot(exprs_cluster, markers = c("m1","m2","m3","m4"))

cytofkit documentation built on Nov. 1, 2018, 3:50 a.m.