volcanoPlot: generates a volcano plot of a data.frame with quantification...
In BenBruyneel/BBPersonalR: BBPersonalR

volcanoPlot

R Documentation

generates a volcano plot of a data.frame with quantification data & statisitcal significance data

Description

generates a volcano plot of a data.frame with quantification data & statisitcal significance data

Usage

volcanoPlot(
  data,
  quantColumn = 1,
  statColumn = 2,
  quantTransform = transformData("log2(data)"),
  statTransform = transformData("-log10(data)"),
  xLabel = ifelse(is.character(quantColumn), paste(c("Log2 ", quantColumn), collapse =
    ""), paste(c("Log2 ", colnames(data)[quantColumn]), collapse = "")),
  yLabel = ifelse(is.character(statColumn), paste(c("-Log10 ", statColumn), collapse =
    ""), paste(c("-Log10 ", colnames(data)[statColumn]), collapse = "")),
  xCutoffs = c(0.5, 2),
  yCutoff = 0.05,
  pointColor = "black",
  significantPointColor = "red",
  pointShape = 21,
  pointSize = 3,
  pointAlpha = 0.75,
  xDefault = TRUE,
  yDefault = TRUE,
  xLimits = c(0, NA),
  yLimits = c(0, NA),
  xExpand = ggplot2::expansion(mult = 0, add = 0),
  yExpand = ggplot2::expansion(mult = 0, add = 0),
  xSymmetric = FALSE,
  xSymmetricExpand = 0.05,
  xCentered = FALSE,
  xMedian = FALSE,
  xDeviations = 4,
  xLabelFormat = ggplot2::waiver(),
  yLabelFormat = ggplot2::waiver(),
  vertical = FALSE,
  title = "",
  gridLines = TRUE,
  volcanoLineMarkers = volcanoLineMarkerDedaults(),
  volcanoLineMarkerAttributes = volcanoMarkerAttributesDefaults(),
  returnData = FALSE,
  significanceColumnName = "",
  removeNonSignificantData = TRUE,
  identifierColumn = NA,
  ...
)

Arguments

`data`	data.frame with at least two columns
`quantColumn`	specifies which column in the data argument contains the quantification data (can be number or character vector)
`statColumn`	specifies which column in the data argument contains the statistical significance data (can be number or character vector). Usually these values are p-values from eg a t-test
`quantTransform`	specifies the function with which to transform the quantColumn data (if needed)
`statTransform`	specifies the function with which to transform the stattColumn data (if needed)
`xLabel`	defines x-axis label
`yLabel`	defines y-axis label
`xCutoffs`	minimum and maximum value of the quantColumn data (before transformation). Anything outside these values and lower than yCutoff will be marked as significant
`yCutoff`	minimum value of the statColumn data. any value lower is marked as significant (usually p-value < 0.05)
`pointColor`	defines the color of the border of the data points
`significantPointColor`	color of the data points that lie outside the xCutoff values and below the yCutoff value
`pointShape`	shape of the data points
`pointSize`	size of the data points
`pointAlpha`	alpha ('see through' value) of the data points
`xDefault`	default is set to TRUE, together with xLimits, this can be used to define the exact range of the X-axis
`yDefault`	default is set to TRUE, together with yLimits, this can be used to define the exact range of the Y-axis
`xLimits`	default = c(0,NA), together with xDefault, this can be used to define the exact range of the Y-axis
`yLimits`	default = c(0,NA), together with yDefault, this can be used to define the exact range of the Y-axis
`xExpand`	allows for padding around data (x-axis), see ?ggplot2::expansion for proper explanation
`yExpand`	allows for padding around data (y-axis), see ?ggplot2::expansion for proper explanation
`xSymmetric`	if TRUE then the range of x-axis will be adjusted to be equal on both the left and the right side of the center (transformed x = 0)
`xSymmetricExpand`	allows for padding around data (x-axis), 0.05 means 5 percent (pre-transformation) extra wide x-axis range
`xCentered`	if TRUE, the plot will be 'cemtered' around the either the mean or median x-value
`xMedian`	if TRUE then median and mean absolute deviation (mad) are used for centering the plot along the x-axis; if FALSE then the mean and tge standard deviation are used
`xDeviations`	defines how many deviations the range of the x-axis may differ from the mean or median. Range will be either (median-xDeviationsmad ,median+xDeviationsmad) or (mean - xDeviationssd,mean + xDeviations*sd)
`xLabelFormat`	allows defining how the x-axis ticks etc are displayed (see formatDigits() & formatScientificDigits())
`yLabelFormat`	allows defining how the y-axis ticks etc are displayed (see formatDigits() & formatScientificDigits())
`vertical`	if TRUE then plot will be rotated 90 degrees
`title`	specifies the title
`gridLines`	if TRUE then gridlines are shown
`volcanoLineMarkers`	defines where to place marker lines in the plot
`volcanoLineMarkerAttributes`	defines the attributes of the marker lines
`returnData`	if TRUE then a list with 2 elements is returned. The first element is the data.frame used to generate the graph and the second element is the graph itself
`significanceColumnName`	name to give to the column specifying if a row is significant (TRUE) or (FALSE). If not specified, then the name "significant" will be used
`removeNonSignificantData`	if TRUE, no non-significant data will be returned (usually a smaller data.frame to return). If FALSE then all data will be returned
`identifierColumn`	specifies which columns from data (names -> character vector) should be included in the data.frame returned
`...`	can be used to pass on other arguments to graphAdjust()