RiboQC.plot {ORFik} | R Documentation

## Quality control for pshifted Ribo-seq data

### Description

Combines several statistics from the pshifted reads into a plot:
-1 Coding frame distribution per read length
-2 Alignment statistics
-3 Biotype of non-exonic pshifted reads
-4 mRNA localization of pshifted reads

### Usage

    RiboQC.plot(
      df,
      output.dir = QCfolder(df),
      width = 6.6,
      height = 4.5,
      plot.ext = ".pdf",
      type = "pshifted",
      weight = "score",
      bar.position = "dodge",
      as_gg_list = FALSE,
      BPPARAM = BiocParallel::SerialParam(progressbar = TRUE)
    )

### Arguments

`df` | an ORFik `experiment`
`output.dir` | NULL or character path, default: NULL, plot not saved to disc. If defined saves plot to that directory with the name "/STATS_plot.pdf".
`width` | width of plot, default 6.6 (in inches)
`height` | height of plot, default 4.5 (in inches)
`plot.ext` | character, default: ".pdf". Alternatives: ".png" or ".jpg".
`type` | type of library loaded, default pshifted, warning if not pshifted might crash if too many read lengths!
`weight` | which column in reads describe duplicates, default "score".
`bar.position` | character, default "dodge". Should Ribo-seq frames per read length be positioned as "dodge" or "stack" (on top of each other).
`as_gg_list` | return as a list of ggplot objects instead of as a grob. Gives you more modification options.
`BPPARAM` | how many cores/threads to use? default: bpparam(). To see number of threads used, do `bpparam()$workers`. You can also add a time remaining bar, for a more detailed pipeline.

### Value

the plot object, a grob of ggplot objects of the the data

### Examples

    df <- ORFik.template.experiment()
    df <- df[3,] #lets only p-shift RFP sample at index 3
    #shiftFootprintsByExperiment(df)
    #RiboQC.plot(df)

[Package ORFik version 1.14.7 Index]