build.plotter {QoRTs}R Documentation

Generating plotters

Description

Generating QC_Plotter objects, which can be used in many of the QoRT utilities to organize samples in various ways to allow for easy comparison and detection of consistent biases and artifacts.

Usage

  build.plotter.basic(res, plotter.params = list())

  build.plotter.colorByGroup(res, plotter.params = list())
  
  build.plotter.colorByLane(res, plotter.params = list())
  
  build.plotter.colorBySample(res, plotter.params = list())
  
  build.plotter.highlightSample(curr.sample,
                                  res,
                                  plotter.params = list(),
                                  merge.offset.outgroup = TRUE)
                                  
  build.plotter.highlightSample.colorByLane(curr.sample,
                                  res,
                                  plotter.params = list(),
                                  merge.offset.outgroup = TRUE,
                                  lane.column.name = "lane.ID")

  build.plotter.colorByX(res, color.by.name,
                         color.by.title.name = color.by.name, 
                         plotter.params = list())

  build.plotter.advanced(res, 
                         colorBy = NULL,
                         color.title = "?",
                         highlightBy = NULL, 
                         highlight = "CURR", 
                         highlightTitle.singular = NULL,
                         highlightTitle.plural = highlightTitle.singular,
                         outgroup.title = "Other",
                         plotter.params = list())

Arguments

res

A QoRT_QC_Results object, created by read.qc.results.data.

curr.sample

A character string. For the sample highlight summary plots, this should be the sample.ID of the sample that is to be highlighted.

merge.offset.outgroup

(For advanced users) A logical value. For the sample highlight plots, determines whether the all lanes that do not include the current sample should be treated as a single "outgroup".

plotter.params

(For advanced users) A named list. Allows you to specify colors, offsets, and other similar patterns. By default these will all be set to reasonable values, however, if you want more control over colors, line-transparency, point plotting characters, or similar, then you can specify a named list.

Any parameters that are not specified in the plotter.params list will be left as default.

Legal parameters are:

  • "contrasting.colors": colors to use for contrast. By default these are set to a series of reasonably-contrasting colors. However, if you have too many different categories then it may be hard to tell some colors apart.

  • "contrasting.pch": point types to use for contrast (see pch in graphical parameters). By default this is set to the basic point types, then following through the upper and lower case letters.

  • "std.color": Color to use for the "highlighted" replicates.

  • "std.lines.lty": Line type to use for the "highlighted" replicates. (see lty in graphical parameters)

  • "std.lines.lwd": Line width to use for the "highlighted" replicates. (see lwd in graphical parameters)

  • "std.lines.alpha": Alpha transparency value to use on lines for the "highlighted" replicates. Numeric value between 0 and 255.

  • "std.points.pch": Character to use for points for the "highlighted" replicates. (see pch in graphical parameters)

  • "std.points.alpha": Alpha transparency value to use on points for the "highlighted" replicates. Numeric value between 0 and 255.

  • "std.points.color": Color to use for the "highlighted" replicates.

  • "std.NVC.colors": A named list with elements named "A", "T", "C", and "G", with each element specifying a color. The colors used to indicate each base for the "highlighted" replicates in the nucleotide-rate-by-position plots.

  • "alt.color": Color to use for the "non-highlighted" replicates.

  • "alt.lines.lty": Line type to use for the "non-highlighted" replicates. (see lty in graphical parameters)

  • "alt.lines.lwd": Line width to use for the "non-highlighted" replicates. (see lwd in graphical parameters)

  • "alt.lines.alpha": Alpha transparency value to use on lines for the "non-highlighted" replicates. Numeric value between 0 and 255.

  • "alt.points.pch": Character to use for points for the "non-highlighted" replicates. (see pch in graphical parameters)

  • "alt.points.alpha": Alpha transparency value to use on points for the "non-highlighted" replicates. Numeric value between 0 and 255.

  • "alt.NVC.colors": A named list with elements named "A", "T","C", and "G", with each element specifying a color. The colors used to indicate each base for the "non-highlighted" replicates in the nucleotide-rate-by-position plots.

  • "show.legend": DEPRECIATED. Currently nonfunctional.

color.by.name

(For advanced users) A character string. (TODO: document functionality)

color.by.title.name

(For advanced users) A character string. (TODO: document functionality)

lane.column.name

The name of the column in the decoder containing the "lane" names.

colorBy

A named character vector. Each unique colorBy string will be assigned a unique color. The names of colorBy must match res@decoder$unique.ID, and must be in the same order.

color.title

A character string. This is the title of the colorby category, used in the titles and figure legends.

highlightBy

A named character vector. Used to determine which replicates to highlight. The names of colorBy must match res@decoder$unique.ID, and must be in the same order.

highlight

A character string. Replicates where highlight equals highlightBy will be highlighted.

highlightTitle.singular

A character string. The singular form of the name of the category highlighted.

highlightTitle.plural

A character string. The plural form of the name of the category highlighted.

outgroup.title

A character string. The description of the non-highlighted category. Used in the figure legends.

Value

A QoRT_Plotter reference object used to create QC summary plots. Depending on which plotter is used, samples/lane-bams can be organized by group, sample, lane, or any arbitrary variable found in the decoder.

See Also

read.qc.results.data

Examples

data(res,package="QoRTsExampleData");
plotter.basic <- build.plotter.basic(res);
makePlot.insert.size(plotter.basic);

## Starting: Insert Size plot.

## Finished: Insert Size plot.[time: 2018-09-25 13:11:45],[elapsed: 0.25 secs]

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plotter.colorByGroup <- build.plotter.colorByGroup(res);
makePlot.insert.size(plotter.colorByGroup);

## Starting: Insert Size plot.

## Finished: Insert Size plot.[time: 2018-09-25 13:11:45],[elapsed: 0.28 secs]

makePlot.legend.over("topright",plotter.colorByGroup);

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plotter.colorByLane <- build.plotter.colorByLane(res);
makePlot.insert.size(plotter.colorByLane);

## Starting: Insert Size plot.

## Finished: Insert Size plot.[time: 2018-09-25 13:11:46],[elapsed: 0.25 secs]

makePlot.legend.over("topright",plotter.colorByLane);

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plotter.colorBySample <- build.plotter.colorBySample(res);
makePlot.insert.size(plotter.colorBySample);

## Starting: Insert Size plot.

## Finished: Insert Size plot.[time: 2018-09-25 13:11:46],[elapsed: 0.27 secs]

makePlot.legend.over("topright",plotter.colorBySample);

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plotter.HS <- build.plotter.highlightSample("SAMP1",
                                            res);
makePlot.insert.size(plotter.HS);

## Starting: Insert Size plot.

## Finished: Insert Size plot.[time: 2018-09-25 13:11:46],[elapsed: 0.28 secs]

makePlot.legend.over("topright",plotter.HS);

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plotter.HSCBL <- build.plotter.highlightSample.colorByLane("SAMP1",
                                                           res);

## list()

makePlot.insert.size(plotter.HSCBL);

## Starting: Insert Size plot.

## Finished: Insert Size plot.[time: 2018-09-25 13:11:47],[elapsed: 0.29 secs]

makePlot.legend.over("topright",plotter.HSCBL);

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#FOR ADVANCED USERS:
#  With the build.plotter.advanced function, you can
#  set coloring and highlighting to match anything you
#  want.
#  The parameters are a little more complex...

#In order to control color, you must create a named
#  vector with names equal to the unique.ID's
#  in the decoder, and in the same order:
#  (this requirement is purely to prevent mistakes)

#For example: to color each sample differently:
colorBy <- res@decoder$sample.ID
names(colorBy) <- res@decoder$unique.ID;

plotter <- build.plotter.advanced(res, colorBy = colorBy);
makePlot.insert.size(plotter);

## Starting: Insert Size plot.

## Finished: Insert Size plot.[time: 2018-09-25 13:11:47],[elapsed: 0.26 secs]

makePlot.legend.over("topright",plotter);

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#Now, to highlight a subgroup of the dataset, you
#  must set the "highlightBy" parameter to a 
#  named vector with names equal to the decoder 
#  unique.ID's, and in the same order.
#  (this requirement is purely to prevent mistakes)
#Then you must tell the plotter which subgroup
#  you want to highlight using the "highlight" 
#  parameter.

#For example, to highlight all lanebams in lane L1:
highlightBy <- res@decoder$lane.ID
names(highlightBy) <- res@decoder$unique.ID;

plotter <- build.plotter.advanced(res, 
                                 highlightBy = highlightBy,
                                 highlight = "L1");
makePlot.insert.size(plotter);

## Starting: Insert Size plot.

## Finished: Insert Size plot.[time: 2018-09-25 13:11:47],[elapsed: 0.28 secs]

makePlot.legend.over("topright",plotter);

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#Other parameters are available to change the title
# and legends:
plotter <- build.plotter.advanced(res, 
                                 highlightBy = highlightBy,
                                 highlight = "L1",
                                 highlightTitle.singular = "Lane",
                                 highlightTitle.plural  = "Lanes",
                                 outgroup.title = "Other");
makePlot.insert.size(plotter);

## Starting: Insert Size plot.

## Finished: Insert Size plot.[time: 2018-09-25 13:11:48],[elapsed: 0.43 secs]

makePlot.legend.over("topright",plotter);

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#You can also color and highlight together.
#  If you do this, only the "highlighted" group will be
#  colored, all the others will be colored gray and will be 
#  drawn in the background. This can be useful for finding
#  biases that are restricted to a subset of the data.

plotter <- build.plotter.advanced(res, 
  colorBy = colorBy,
  highlightBy = highlightBy,
  highlight = "L1",
  color.title = "sample",
  highlightTitle.singular = "Lane",
  highlightTitle.plural = "Lanes",
  outgroup.title = "Other"
);
makePlot.insert.size(plotter);

## Starting: Insert Size plot.

## Finished: Insert Size plot.[time: 2018-09-25 13:11:48],[elapsed: 0.28 secs]

makePlot.legend.over("topright",plotter);

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#You can make multiplots using a given plotter object by
# using the "makeMultiPlot.withPlotter" function:

#makeMultiPlot.withPlotter(plotter);
[Package QoRTs version 1.3.6 Index]