cytof_progressionPlot {cytofkit} | R 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"))

[Package cytofkit version 1.12.0 Index]