plot.subsamples {subSeq} | R Documentation

## plot metrics as a function of subsampled read depth

### Description

Plot the number of genes found significant, the Spearman correlation of the effect size estimates with the full experiment, and the empirical false discovery rate as a function of the subsampled read depth. This determines whether these metrics saturate, which indicates that the experiment has an appropriate sequencing depth.

### Usage

    ## S3 method for class 'subsamples'
    plot(x, ...)

### Arguments

`x` | a `subsamples` object
`...` | further arguments passed to or from other methods.

### Details

This is an alias for the plot.summary.subsamples function, so that plotting can be done directly on the subsamples object. We recommend using `summary(ss)` first, so that the summary operation does not have to be performed each time the figure is plotted, and so the summary object can be examined on its own.

### Value

plot a subSeq object

### Examples

    if (interactive()) {
    # import the subsampling object (see ?subsample to see how ss is created)
    data(ss)

    # plot subsample object
    plot(ss)
    }

[Package subSeq version 1.18.0 Index]