Create a summary heatmap

Create a summary heatmap. The input arguments for this functions are typically generated using bettrGetReady, which ensures that all required columns are available.

makeHeatmap(
  bettrList = NULL,
  plotdata,
  scoredata,
  idCol,
  metricCol = "Metric",
  valueCol = "ScaledValue",
  weightCol = "Weight",
  scoreCol = "Score",
  metricGroupCol = "metricGroup",
  metricInfo,
  metricColors,
  idInfo,
  idColors,
  metricCollapseGroup = FALSE,
  metricGrouping = "---",
  labelSize = 10,
  showRowNames = TRUE,
  plotType = "Heatmap",
  rownamewidth_cm = 6,
  colnameheight_cm = 6
)

Arguments

bettrList

A list, the output object from prepData. If bettrList is provided, arguments plotdata, scoredata, idCol, metricCol, valueCol, weightCol, scoreCol, metricGroupCol, metricInfo, metricColors, idInfo, idColors, metricCollapseGroup, metricGrouping and methods will be ignored and the corresponding values will be extracted from bettrList. This is the recommended way of calling the plotting functions, as it ensures compatibility of all components.

plotdata

A data.frame with columns representing methods, metrics, scores, and weights. Typically obtained as prepData$plotdata, where prepData is the output from bettrGetReady.

scoredata

A data.frame with columns representing methods, aggregated scores, and any other method annotations. Typically obtained as prepData$scoredata, where prepData is the output from bettrGetReady.

idCol

Character scalar indicating which column of plotdata and scoredata contains the method IDs.

metricCol

Character scalar indicating which column of plotdata contains the metric IDs. Typically, "Metric".

valueCol

Character scalar indicating which column of plotdata contains the metric values. Typically, "ScaledValue".

weightCol

Character scalar indicating which column of plotdata contains the weight values. Typically, "Weight".

scoreCol

Character scalar indicating which column of scoredata contains the aggregated score values. Typically, "Score".

metricGroupCol

Character scalar indicating which column of plotdata contains the information about the metric group. Typically, "metricGroup".

metricInfo

data.frame with annotations for metrics. Typically obtained as prepData$metricInfo, where prepData is the output from bettrGetReady.

metricColors

Named list with colors used for the metrics and any other metric annotations. Typically obtained as prepData$metricColors, where prepData is the output from bettrGetReady.

idInfo

data.frame with annotations for entities. Typically obtained as prepData$idInfo, where prepData is the output from bettrGetReady.

idColors

Named list with colors used for methods and any other method annotations. Typically obtained as prepData$idColors, where prepData is the output from bettrGetReady.

metricCollapseGroup

Logical scalar indicating whether metrics should be collapsed by the group variable provided by metricGrouping. Typically obtained as prepData$metricCollapseGroup, where prepData is the output from bettrGetReady.

metricGrouping

Character scalar indicating the column of metricInfo that was used to group metrics. Typically obtained as prepData$metricGrouping, where prepData is the output from bettrGetReady.

labelSize

Numeric scalar providing the size of the labels in the plot.

showRowNames

Logical scalar indicating whether to show row (method) names in the heatmap.

plotType

Either "Heatmap" or "Dot plot" indicating the type of plot to construct.

rownamewidth_cm, colnameheight_cm

Numeric scalars defining the width of row names and height of column names, in cm.

Value

A HeatmapList object.

Author

Charlotte Soneson

Examples

## Generate example data
df <- data.frame(Method = c("M1", "M2", "M3"), 
                 metric1 = c(1, 2, 3),
                 metric2 = c(3, 1, 2))
metricInfo <- data.frame(Metric = c("metric1", "metric2", "metric3"),
                         Group = c("G1", "G2", "G2"))
idInfo <- data.frame(Method = c("M1", "M2", "M3"), 
                     Type = c("T1", "T1", "T2"))
prepData <- bettrGetReady(df = df, idCol = "Method", 
                          metricInfo = metricInfo, idInfo = idInfo)
makeHeatmap(bettrList = prepData, plotType = "Heatmap")

makeHeatmap(bettrList = prepData, plotType = "Dot plot")