hoeffDPlot {MatrixQCvis} | R Documentation

## Create a plot from a list of Hoeffding's D values

### Description

The function 'hoeffDPlot' creates via 'ggplot' a violin plot per factor, a jitter plot of the data points and (optionally) connects the points via lines. 'hoeffDPlot' uses the 'plotly' package to make the figure interactive.

### Usage

    hoeffDPlot(df, lines = TRUE)

### Arguments

`df` | 'data.frame' containing one or multiple columns containing the Hoeffding's D statistics
`lines` | 'logical', should points belonging to the same sample be connected

### Details

The function 'hoeffDPlot' will create the violin plot and jitter plot according to the specified order given by the colnames of 'df'. 'hoeffDPlot' will thus internally refactor the 'colnames' of the supplied 'data.frame' according to the order of the 'colnames'.

### Value

'gg' object from 'ggplot2'

### Examples

    ## create se
    set.seed(1)
    a <- matrix(rnorm(10000), nrow = 1000, ncol = 10,
                dimnames = list(1:1000, paste("sample", 1:10)))
    a[c(1, 5, 8), 1:5] <- NA
    cD <- data.frame(name = colnames(a), type = c(rep("1", 5), rep("2", 5)))
    rD <- data.frame(spectra = rownames(a))
    se <- SummarizedExperiment::SummarizedExperiment(assay = a,
        rowData = rD, colData = cD)

    tbl <- MAvalues(se, log2 = FALSE, group = "all")
    hd_r <- hoeffDValues(tbl, "raw")

    ## normalized values
    se_n <- se
    assay(se_n) <- normalizeAssay(a, "sum")
    tbl_n <- MAvalues(se_n, log2 = FALSE, group = "all")
    hd_n <- hoeffDValues(tbl_n, "normalized")

    df <- data.frame(raw = hd_r, normalized = hd_n)
    hoeffDPlot(df, lines = TRUE)
    hoeffDPlot(df, lines = FALSE)

[Package MatrixQCvis version 1.0.0 Index]