plotLfcGC-methods: Method plotLfcGC

In exomePeak2: Bias Awared Peak Calling and Quantification for MeRIP-Seq

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,
  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,
  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.
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)

exomePeak2 documentation built on Nov. 8, 2020, 5:27 p.m.