hanabiPlot {CAGEr} | R Documentation

## hanabiPlot

### Description

Plot feature discovery curves

### Usage

    hanabiPlot(x, group, col = NULL, legend.pos = "topleft", pch = 1, ...)

### Arguments

`x` | A hanabi object.
`group` | A character vector or a factor grouping the samples.
`col` | A character vector colors (at most one per group).
`legend.pos` | Position of the legend, passed to the `legend` function.
`pch` | Plot character at the tip of the lines and in the legend.
`...` | Further arguments to be passed to the `plot.hanabi` function.

### Details

Plots the number of features (genes, transcripts, ...) detected for a given number of counts (reads, unique molecules, ...). Each library is sub-sampled by rarefaction at various sample sizes, picked to provide enough points so that the curves look smooth. The final point is plotted as an open circle, hence the name "hanabi", which means fireworks in Japanese.

The rarefactions take time to do, so this step is done by a separate function, so that the result is easily cached.

### Author(s)

Charles Plessy

### See Also

Other CAGEr richness functions: `hanabi`, `plot.hanabi`

Other CAGEr richness functions: `hanabi`, `plot.hanabi`

Other CAGEr plot functions: `plotAnnot`, `plotCorrelation`, `plotExpressionProfiles`, `plotInterquantileWidth`, `plotReverseCumulatives`

### Examples

    h <- hanabi(CTSStagCountDF(exampleCAGEexp))
    hanabiPlot(h, group = 1:5)
    hanabiPlot(hanabi(CTSStagCountDF(exampleCAGEexp), n = 20, step = 0.8, from = 25000), group = 1:5)
    hanabiPlot(hanabi(CTSStagCountDF(exampleCAGEexp), n = 10, step = 0.98), group = 1:5)
    hanabiPlot(h, group=c("A", "A", "B", "C", "B"), col=c("red", "green", "blue"))
    hanabiPlot(h, group = 1:5, pch=1:5, col="purple")

[Package CAGEr version 1.24.0 Index]