compareAlgs: Compare scoring algorithms on a single signature via heatmap...
In TBSignatureProfiler: Profile RA-Seq Data Using TB Pathway Signatures

Description Usage Arguments Value Examples

It may be useful to compare the results of scoring across several different scoring algorithms via a method of visualization, such as a heatmap. The compareSigs function allows the input of a SummarizedExperiment data object and conducts profiling on each signature desired, and outputting a heatmap or boxplot for each signature.

compareAlgs(
  input,
  signatures = NULL,
  annotationColName,
  useAssay = "counts",
  algorithm = c("GSVA", "ssGSEA", "ASSIGN", "PLAGE", "Zscore", "singscore"),
  showColumnNames = TRUE,
  showRowNames = TRUE,
  scale = FALSE,
  colorSets = c("Set1", "Set2", "Set3", "Pastel1", "Pastel2", "Accent", "Dark2",
    "Paired"),
  choose_color = c("blue", "gray95", "red"),
  colList = list(),
  show.pb = FALSE,
  parallel.sz = 0,
  output = "heatmap",
  num.boot = 100
)

`input`	an input data object of the class `"SummarizedExperiment"`. Required.
`signatures`	a `list` of signatures to run with their associated genes. This list should be in the same format as `TBsignatures`, included in the TBSignatureProfiler package. If `signatures = NULL`, the default set of signatures `TBsignatures` list is used. For details, run `?TBsignatures`. The default is `NULL`.
`annotationColName`	a character string giving the column name in `colData` that contains the annotation data. Required.
`useAssay`	a character string specifying the assay to use for signature profiling when `input` is a `SummarizedExperiment`. Required only for input data of the class `SummarizedExperiment`. If null, the assay used will be `"counts"`. The default is `NULL.`
`algorithm`	a vector of algorithms to run, or character string if only one is desired. The default is `c("GSVA", "ssGSEA", "ASSIGN", "PLAGE", "Zscore", "singscore")`.
`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`.
`scale`	logical. Setting `scale = TRUE` scales the signature data. The default is `FALSE`.
`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")`.
`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.
`show.pb`	logical, whether warnings and other output from the profiling should be suppressed (including progress bar output). Default is `FALSE`.
`parallel.sz`	an integer identifying the number of processors to use when running the calculations in parallel for the GSVA and ssGSEA algorithms. If `parallel.sz = 0`, all cores are used. The default is `0`.
`output`	a character string specifying whether the outputted plot should be a `"heatmap"` or `"boxplot"`. The default is `"heatmap"`.
`num.boot`	an integer indicating the number of times to bootstrap the data.

A heatmap or boxplot for each signature specified comparing the enumerated algorithms.

# Example using the TB_hiv data set, two signatures, and 3 algorithms
data("TB_hiv")
compareAlgs(TB_hiv, signatures = TBsignatures[c(1,2)],
            annotationColName = "Disease",
            algorithm = c("GSVA", "ssGSEA", "PLAGE"),
            scale = TRUE, parallel.sz = 1, output = "heatmap")