plotCIs {Rariant} | R Documentation

## Plotting Functions

### Description

The 'plotConfidenceIntervals' is a high-level plotting function for visualizing confidence intervals. The 'plotAbundanceShift' function visualizes the shift in mismatch rates between two samples.

### Usage

    plotConfidenceIntervals(x, ylim = c(-1.05, 1.05), color = NULL, ...)

    plotAbundanceShift(x, ylim = c(-0.05, 1.05), rates = TRUE, ...)

### Arguments

`x` | 'GRanges' with mcols of a CI method, or 'data.frame' as returned by one of the CI methods, with the optional column 'start'.
`ylim` | Limits of the y-axis. Using this instead of using the 'ylim' prevents ugly warnings of 'ggplot2'.
`color` | Variable that determines the coloring of the confidence axis (character).
`rates` | Should the non-consensus rates of both samples be visualized as colored end points of the line range? (logical, default: TRUE).
`...` | Additional plotting arguments that are passed on to ggplot2::geom_pointrange.

### Value

For a 'GRanges' input: A 'ggbio' object

For a 'data.frame' input: A 'ggplot' object

### Examples

    ## Generate sample data
    counts = data.frame(x1 = 1:5, n1 = 30, x2 = 0:4, n2 = 30)

    ## Agresti-Caffo
    ci_ac = with(counts, acCi(x1, n1, x2, n2))

    library(GenomicRanges)
    gr = GRanges("1", IRanges(start = 1:nrow(counts), width = 1))
    mcols(gr) = ci_ac

    ## GRanges
    plotConfidenceIntervals(gr)

    ## data.frame
    plotConfidenceIntervals(ci_ac)

    ## abundance shift
    plotAbundanceShift(gr)

    plotAbundanceShift(ci_ac)

[Package Rariant version 1.20.0 Index]