R: Plot Alignment Clipping

makePlot.norm.factors {QoRTs}

R Documentation

Plot Alignment Clipping

Description

Plots the rate at which the aligner soft-clips off portions of aligned reads.

Usage

  makePlot.norm.factors(plotter, by.sample = TRUE, 
                return.table = FALSE,
                debugMode, singleEndMode,
                plot = TRUE,
                ...)
  makePlot.norm.factors.vs.TC(plotter, 
                by.sample = TRUE, 
                return.table = FALSE,
                debugMode, singleEndMode,
                plot = TRUE,
                ...)

Arguments

`plotter`	A `QoRT_Plotter` reference object. See `build.plotter`.
`by.sample`	Logical. Whether to combine all lanebams for each sample before calculating normalization factors. By default, normalization factors for each lanebam will be calculated seperately.
`return.table`	Logical. Whether to return a data table containing the data that is plotted.
`debugMode`	Logical. If TRUE, debugging data will be printed to the console.
`singleEndMode`	Logical. Determines whether the dataset consists of single-ended reads. By default this is determined from the data. Thus, this parameter should never need to be set by the user.
`plot`	Logical. If FALSE, suppress plotting and return `TRUE` if and only if the data is present in the dataset to allow plotting. Useful to automatically filter out missing data plots.
`...`	Arguments to be passed to methods, such as graphical parameters (see `par`).

Details

makePlot.norm.factors plots the normalization factors for each sample/lanebam. Note that unless DESeq2 and edgeR are installed, it will only plot total-count normalization by default. Also note that unless calc.DESeq2 = TRUE and/or calc.edgeR = TRUE in the execution of the read.qc.results.data that produced the QC results, only the total counts normalization factors will be calculated.

makePlot.norm.factors.vs.TC plots the ratio of alternative normalization factors against the total count normalization.

Value

Usually returns nothing, unless return.table is TRUE, in which case it returns a data.frame containing the plotted data for each sample.

Examples

  data(res,package="QoRTsExampleData");
  plotter <- build.plotter.colorByGroup(res);
  makePlot.norm.factors(plotter);

## Starting: Normalization Factors plot.

## Warning: Skipping Normalization Factors plotting. Data not found!

  makePlot.norm.factors.vs.TC(plotter);

## Starting: Normalization Factors plot.
## Warning: Skipping Normalization Factors plotting. Data not found!

plot of chunk unnamed-chunk-1

  #Legend:
  makePlot.legend.box(plotter);