signatureHeatmap: Plot a heatmap of signature scores.
In TBSignatureProfiler: Profile RA-Seq Data Using TB Pathway Signatures

Description Usage Arguments Details Value Examples

This function takes a dataset of scored gene expression data as an input and returns a ComplexHeatmap plot for for visual comparison of signature performance.

signatureHeatmap(
  inputData,
  annotationData = NULL,
  name = "Signatures",
  signatureColNames,
  annotationColNames = NULL,
  colList = list(),
  scale = FALSE,
  showColumnNames = TRUE,
  showRowNames = TRUE,
  colorSets = c("Set1", "Set2", "Set3", "Pastel1", "Pastel2", "Accent", "Dark2",
    "Paired"),
  choose_color = c("blue", "gray95", "red"),
  split_heatmap = "disease",
  annotationSignature = sigAnnotData,
  ...
)

`inputData`	an input data object. It should either be of the class `SummarizedExperiment` and contain the profiled signature data and annotation data as columns in the colData, or alternatively be of the classes `data.frame` or `matrix` and contain only the gene expression data. Required.
`annotationData`	a `data.frame` or `matrix` of annotation data, with one column. Only required if `inputData` is a `data.frame` or `matrix` of signature data. The row names must equal those of the `inputData` column names. Default is `NULL`.
`name`	a character string with the plot title of the heatmap. The default is `"Signatures"`.
`signatureColNames`	a vector of the column names in `colData` that contain the signature data. Only required if `inputData` is a SummarizedExperiment object.
`annotationColNames`	a vector of the column names in `colData` that contain the annotation data. Only required if `inputData` is a `SummarizedExperiment`. Default is `NULL`.
`colList`	a named `list` of named vectors specifying custom color information to pass to `ComplexHeatmap::Heatmap()`. The list should have as many elements as there are annotation columns, and each element name should correspond exactly with the name of each annotation column. The colors in the vector elements should be named according to the levels of the factor in that column's annotation data if the annotation is discrete, or it should be produced with `circlize::colorRamp2` if the annotation is continuous. By default, `ColorBrewer` color sets will be used. See the the parameter `colorSets` for additional details.
`scale`	logical. Setting `scale = TRUE` scales the signature data. The default is `FALSE`.
`showColumnNames`	logical. Setting `showColumnNames = TRUE` will show the column names (i.e. sample names) on the heatmap. The default is `TRUE`.
`showRowNames`	logical. Setting `showColumnNames = TRUE` will show the row names (i.e. signature names) on the heatmap. The default is `TRUE`.
`colorSets`	a vector of names listing the color sets in the order that they should be used in creating the heatmap. By default, this function will use the color sets in the order listed in `Usage` for annotation information. You may replace the default with the same collection of sets in order that you want to use them, or provide custom color sets with the `colList` parameter.
`choose_color`	a vector of color names to be interpolated for the heatmap gradient, or a `colorRamp` function produced by `circlize::colorRamp2`. The default is `c("blue", "gray95", "red")`.
`split_heatmap`	a character string either giving the column title of `annotationSignature` containing annotation data for which to split the heatmap rows (i.e., signatures), or `"none"` if no split is desired. The default is `"disease"`.
`annotationSignature`	a `data.frame` or `matrix` with information to be used in splitting the heatmap. The first column should signature names. The column of annotation information should be specified in `split_heatmap.` Other columns will be ignored. The default is `sigAnnotData`.
`...`	Additional arguments to be passed to `ComplexHeatmap::Heatmap()`.

If both annotationData = NULL and annotationColNames = NULL, no annotation bar will be drawn on the heatmap.

A ComplexHeatmap plot.

library(SummarizedExperiment)
# Generate some artificial data that shows a difference in Zak_RISK_16
mat_testdata <- rbind(matrix(c(rnorm(80), rnorm(80) + 5), 16, 10,
                             dimnames = list(TBsignatures$Zak_RISK_16,
                                             paste0("sample", seq_len(10)))),
                      matrix(rnorm(1000), 100, 10,
                             dimnames = list(paste0("gene", seq_len(100)),
                                             paste0("sample", seq_len(10)))))
# Create a SummarizedExperiment object that contains the data
testdataSE <- SummarizedExperiment(assays = SimpleList(data = mat_testdata),
                                     colData = DataFrame(sample =
                                                           c(rep("down", 5),
                                                                rep("up", 5))))
res <- runTBsigProfiler(testdataSE, useAssay = "data",
                        signatures = TBsignatures["Zak_RISK_16"],
                        algorithm = c("GSVA", "ssGSEA"), parallel.sz = 1,
                        combineSigAndAlgorithm = TRUE)
signatureHeatmap(res, signatureColNames = c("GSVA_Zak_RISK_16",
                                            "ssGSEA_Zak_RISK_16"),
                 annotationColNames = "sample", scale = TRUE,
                 showColumnNames = FALSE, split_heatmap = "none")

# Example using custom colors for the annotation information
color2 <- stats::setNames(c("purple", "black"), c("down", "up"))
color.list <- list("sample" = color2)

signatureHeatmap(res, signatureColNames = c("GSVA_Zak_RISK_16",
                                            "ssGSEA_Zak_RISK_16"),
                 annotationColNames = "sample", scale = TRUE,
                 showColumnNames = FALSE,
                 colList = color.list, split_heatmap = "none")