hist: Density estimate

In benilton/oligo-release: Preprocessing tools for oligonucleotide arrays.

Description

Plot the density estimates for each sample

Usage

## S4 method for signature 'FeatureSet'
hist(x, transfo=log2, which=c("pm", "mm", "bg", "both", "all"),
                   nsample=10000, ...)

## S4 method for signature 'ExpressionSet'
hist(x, transfo=identity, nsample=10000, ...)

Arguments

x	FeatureSet or ExpressionSet object
transfo	a function to transform the data before plotting. See 'Details'.
nsample	number of units to sample and build the plot.
which	set of probes to be plotted ("pm", "mm", "bg", "both", "all").
...	arguments to be passed to matplot

Details

The 'transfo' argument will set the transformation to be used. For raw data, 'transfo=log2' is a common practice. For summarized data (which are often in log2-scale), no transformation is needed (therefore 'transfo=identity').

Note

The hist methods for FeatureSet and Expression use a sample (via sample) of the probes/probesets to produce the plot (unless nsample > nrow(x)). Therefore, the user interested in reproducibility is advised to use set.seed.

benilton/oligo-release documentation built on May 12, 2019, 10:59 a.m.