This script allows you to perform PCA plot visualization using the results of the MetaProViz analysis PCA plot visualization

Usage

VizPCA(
  InputData,
  SettingsInfo = NULL,
  SettingsFile_Sample = NULL,
  ColorPalette = NULL,
  ColorScale = "discrete",
  ShapePalette = NULL,
  ShowLoadings = FALSE,
  Scaling = TRUE,
  Theme = NULL,
  PlotName = "",
  SaveAs_Plot = "svg",
  PrintPlot = TRUE,
  FolderPath = NULL
)

Arguments

SettingsInfo: Optional: NULL or Named vector including at least one of those three information : c(color="ColumnName_Plot_SettingsFile", shape= "ColumnName_Plot_SettingsFile"). Default = NULL
SettingsFile_Sample: Optional: DF which contains information about the samples, which will be combined with your input data based on the unique sample identifiers used as rownames. Column "Conditions" with information about the sample conditions (e.g. "N" and "T" or "Normal" and "Tumor"), can be used for feature filtering and colour coding in the PCA. Column "AnalyticalReplicate" including numerical values, defines technical repetitions of measurements, which will be summarised. Column "BiologicalReplicates" including numerical values. Please use the following names: "Conditions", "Biological_Replicates", "Analytical_Replicates".Default = NULL
ColorPalette: Optional: Provide customiced color-palette in vector format. For continuous scale use e.g. scale_color_gradient(low = "#88CCEE", high = "red") and for discrete scale c("#88CCEE", "#DDCC77","#661100", "#332288")Default = NULL
ColorScale: Optional: Either "continuous" or "discrete" colour scale. For numeric or integer you can choose either, for character you have to choose discrete. Default = NULL
ShapePalette: Optional: Provide customiced shape-palette in vector format. Default = NULL
ShowLoadings: Optional: TRUE or FALSE for whether PCA loadings are also plotted on the PCA (biplot) Default = FALSE
Scaling: Optional: TRUE or FALSE for whether a data scaling is used Default = TRUE
Theme: Optional: Selection of theme for plot, e.g. theme_grey(). You can check for complete themes here: https://ggplot2.tidyverse.org/reference/ggtheme.html. If default=NULL we use theme_classic(). Default = "discrete"
PlotName: Optional: String which is added to the output files of the PCA Default = ""
SaveAs_Plot: Optional: Select the file type of output plots. Options are svg, png, pdf or NULL. Default = svg
PrintPlot: Optional: TRUE or FALSE, if TRUE Volcano plot is saved as an overview of the results. Default = TRUE
FolderPath: Optional: Path to the folder the results should be saved at. default: NULL
Input_data: DF with unique sample identifiers as row names and metabolite numerical values in columns with metabolite identifiers as column names. Use NA for metabolites that were not detected. includes experimental design and outlier column.

Value

List with two elements: Plot and Plot_Sized

Examples

Intra <- ToyData("IntraCells_Raw")[,-c(1:3)]
Res <- VizPCA(Intra)
#> Error in ggplot2::autoplot(stats::prcomp(as.matrix(InputData), scale. = as.logical(Scaling)),     data = InputPCA, colour = Param_Col, fill = Param_Col, shape = Param_Sha,     size = 3, alpha = 0.8, label = T, label.size = 2.5, label.repel = TRUE,     loadings = as.logical(ShowLoadings), loadings.label = as.logical(ShowLoadings),     loadings.label.vjust = 1.2, loadings.label.size = 2.5, loadings.colour = "grey10",     loadings.label.colour = "grey10"): Objects of class <prcomp> are not supported by autoplot.
#> ℹ Have you loaded the required package?