hanabiPlot: hanabiPlot

In charles-plessy/CAGEr: Analysis of CAGE (Cap Analysis of Gene Expression) sequencing data for precise mapping of transcription start sites and promoterome mining

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: TSSlogo(), 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")

charles-plessy/CAGEr documentation built on Oct. 27, 2024, 10:11 p.m.