cytof_progressionPlot: Progression plot

View source: R/cytof_postProcess.R

cytof_progressionPlotR Documentation

Progression plot

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"))

JinmiaoChenLab/cytofkit2 documentation built on May 12, 2022, 8:09 a.m.