VisualizeDesign: Visualize design matrix
In ExploreModelMatrix: Graphical Exploration of Design Matrices

Description Usage Arguments Value Author(s) Examples

View source: R/VisualizeDesign.R

Given a sample table and a design formula, generate a collection of static plots for exploring the resulting design matrix graphically. This function is called internally by ExploreModelMatrix(), but can also be used directly if interactivity is not required.

VisualizeDesign(
  sampleData,
  designFormula,
  flipCoordFitted = FALSE,
  flipCoordCoocc = FALSE,
  textSizeFitted = 5,
  textSizeCoocc = 5,
  textSizeLabsFitted = 12,
  textSizeLabsCoocc = 12,
  lineWidthFitted = 25,
  addColorFitted = TRUE,
  colorPaletteFitted = scales::hue_pal(),
  dropCols = NULL,
  designMatrix = NULL
)

`sampleData`	A `data.frame` of `DataFrame` with sample information.
`designFormula`	A `formula`. All components of the terms must be present as columns in `sampleData`.
`flipCoordFitted, flipCoordCoocc`	A `logical`, whether to flip the coordinate axes in the fitted values/co-occurrence plot, respectively.
`textSizeFitted, textSizeCoocc`	A `numeric` scalar giving the text size in the fitted values/co-occurrence plot, respectively.
`textSizeLabsFitted, textSizeLabsCoocc`	A `numeric` scalar giving the text size for the axis labels in the fitted values/co-occurrence plot, respectively.
`lineWidthFitted`	A `numeric` scalar giving the maximal length of a row in the fitted values plot, before it is split and printed on multiple lines
`addColorFitted`	A `logical` scalar indicating whether the terms in the fitted values plot should be shown in different colors.
`colorPaletteFitted`	A `function` returning a color palette to use for coloring the model coefficients in the fitted values plot.
`dropCols`	A character vector with columns to drop from the design matrix, or NULL if no columns should be dropped.
`designMatrix`	A `numeric` matrix, which can be supplied as an alternative to `designFormula`. Rows must be in the same order as the rows in `sampleData`.

A list with the following elements:

sampledata: A data.frame, expanded from the input sampleData
plotlist: A list of plots, displaying the fitted values for each combination of predictor values, in terms of the model coefficients.
designmatrix: The design matrix, after removing any columns in dropCols
pseudoinverse: The pseudoinverse of the design matrix
vifs: A data.frame with calculated variance inflation factors
colors: A vector with colors to use for different model coefficients
cooccurrenceplots: A list of plots, displaying the co-occurrence pattern for the predictors (i.e., the number of observations for each combination of predictor values)
totnbrrows: The total number of "rows" in the list of plots of fiitted values. Useful for deciding the required size of the plot canvas.

Charlotte Soneson

VisualizeDesign(
  sampleData = data.frame(genotype = rep(c("A", "B"), each = 4),
                          treatment = rep(c("treated", "untreated"), 4)),
  designFormula = ~genotype + treatment
)