plotExonLength-methods {exomePeak2} | R Documentation

## Method plotExonLength

### Description

This function plot the distribution of the exon length for peaks containing exons.

### Usage

    plotExonLength(
      sep,
      txdb = NULL,
      save_pdf_prefix = NULL,
      include_control_regions = TRUE,
      save_dir = "."
    )

    ## S4 method for signature 'SummarizedExomePeak'
    plotExonLength(
      sep,
      txdb = NULL,
      save_pdf_prefix = NULL,
      include_control_regions = TRUE,
      save_dir = "."
    )

### Arguments

`sep` | a `SummarizedExomePeak` object.
`txdb` | a `TxDb` object containing the transcript annotation.
`save_pdf_prefix` | a `character` if provided, a pdf file with the given name will be saved under the current working directory.
`include_control_regions` | a `logical` for whether to include the control regions or not; Default `= TRUE`.
`save_dir` | a `character` for the directory to save the plot; Default `= "."`.

### Details

If the SummarizedExomePeaks object contains LFC statistics, the significantly modified peaks with IP to input log2FC > 0 and GLM Wald test padj < .05 will be plotted .

If the SummarizedExomePeaks object contains interactive LFC statistics, both the hyper modification and hypo modification peaks with GLM Wald test p values < .05 will be plotted.

### Value

a ggplot object

### Examples

    ### Make TxDb object from the gff file
    library(GenomicFeatures)
    GENE_ANNO_GTF = system.file("extdata", "example.gtf", package="exomePeak2")

    txdb <- makeTxDbFromGFF(GENE_ANNO_GTF)

    ### Load the example SummarizedExomPeak object
    f1 = system.file("extdata", "sep_ex_mod.rds", package="exomePeak2")

    sep <- readRDS(f1)

    ### Visualize the linear relationships between GC content and normalized reads count under different regions
    plotExonLength(sep,txdb)

[Package exomePeak2 version 1.2.0 Index]