# Visualize distribution assessment

Source: `R/Plot.R`
`plotEvalDist.Rd`

This function plots the results of `evaluateDist` to assess goodness-of-fit testing.

    plotEvalDist(evalDistRes, Annot=TRUE)

## Arguments

evalDistRes | The output of `evaluateDist`.
Annot | A logical vector. If `TRUE`, a short description of the plot is included.

## Value

A ggplot object.

## Examples

    if (FALSE) {
    ## using example data set, but run it for fraction of genes
    data("CELseq2_Gene_UMI_Counts")
    evalDistRes <- evaluateDist(countData = CELseq2_Gene_UMI_Counts, batchData = NULL,
                                spikeData = NULL, spikeInfo = NULL,
                                Lengths = NULL, MeanFragLengths = NULL,
                                RNAseq = "singlecell", Protocol = "UMI",
                                Normalisation = "scran",
                                GeneFilter = 0.1, SampleFilter = 3,
                                FracGenes = 0.1,
                                verbose = TRUE)
    plotEvalDist(evalDistRes)
    }