plotLfcGC-methods {exomePeak2} | R Documentation

## Method plotLfcGC

### Description

`plotLfcGC` plot the scatter plot between GC content and the (differential) modification LFCs.

### Usage

    plotLfcGC(
      sep,
      bsgenome = NULL,
      txdb = NULL,
      save_pdf_prefix = NULL,
      point_size = 0.05,
      xlim = c(0.2, 0.9),
      fragment_length = 100,
      binding_length = 25,
      effective_GC = FALSE,
      save_dir = "."
    )

    ## S4 method for signature 'SummarizedExomePeak'
    plotLfcGC(
      sep,
      bsgenome = NULL,
      txdb = NULL,
      save_pdf_prefix = NULL,
      point_size = 0.05,
      xlim = c(0.2, 0.9),
      fragment_length = 100,
      binding_length = 25,
      effective_GC = FALSE,
      save_dir = "."
    )

### Arguments

`sep` | a `SummarizedExomePeak` object.
`bsgenome` | a `BSgenome` object for the genome sequence, it could be the name of the reference genome recognized by `getBSgenome`.
`txdb` | a `TxDb` object for the transcript annotation, it could be the name of the reference genome recognized by `makeTxDbFromUCSC`.
`save_pdf_prefix` | a `character`, if provided, a pdf file with the given name will be saved under the current directory; Default `= NULL`.
`point_size` | a `numeric` value for the point size of the scatter plot; Default `= 0.05`.
`xlim` | a `numeric` vector for the range of x-axis of the plot; Default `= c(0.2,0.9)`.
`fragment_length` | a `numeric` value for the expected fragment length in the RNA-seq library; Default `= 100`.
`binding_length` | a `numeric` value for the expected antibody binding length in IP samples; Default `= 25`.
`effective_GC` | a `logical` value of whether to calculate the weighted GC content by the probability of reads alignment; default `= FALSE`.
`save_dir` | a `character` for the directory to save the plot; default ".".

### Details

By default, this function will generate a scatter plot between GC content and the log2FC value. The significant modification sites will be lebeled in different colours.

### Value

a `ggplot` object.

### Examples

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

    sep <- readRDS(f1)

    ### Visualize the relationship between GC content and the (differential) LFC
    plotLfcGC(sep)

[Package exomePeak2 version 1.6.1 Index]