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Plot the quality control of a nacho object

Source: R/autoplot.R
autoplot.nacho.Rd

Draws any of the quality-control figures of the Shiny app (visualise()) and of the HTML or PDF report (render()).

Value

A ggplot object.

Usage

autoplot(
  object,
  type,
  colour = "CartridgeID",
  size = 0.5,
  show_legend = TRUE,
  show_outliers = TRUE,
  outliers_factor = 1,
  outliers_labels = NULL,
  dark = FALSE
)

Arguments

  • object: A nacho object from load_rcc() or normalise().

  • type: The plot to draw, one of:

    • "BD": Binding Density.

    • "FoV": Field of View (imaging).

    • "PCL": Positive Control Linearity.

    • "LoD": Limit of Detection.

    • "Positive": Positive controls.

    • "Negative": Negative controls.

    • "Housekeeping": Housekeeping genes.

    • "PN": Positive controls against negative controls.

    • "ACBD": Average counts against binding density.

    • "ACMC": Average counts against median counts.

    • "PCA12": Principal component 1 against 2.

    • "PCAi": Scree plot of the principal components.

    • "PCA": Planes of the first principal components.

    • "PFNF": Positive factor against negative factor.

    • "HF": Housekeeping factor.

    • "NORM": Normalisation factor.

    • "Stability": geNorm stability of the housekeeping genes, see housekeeping_stability(). The dashed line marks M = 1.5, the limit geNorm suggests for homogeneous samples. This plot ignores colour, show_legend, show_outliers and outliers_labels.

    • "RLE": Relative log expression of the normalised endogenous genes. This plot ignores size, show_outliers, outliers_factor and outliers_labels.

    • "BatchFactors": Normalisation factors by cartridge. This plot ignores show_outliers, outliers_factor and outliers_labels.

    • "PCBatch": Share of each principal component explained by cartridge and date; see batch_diagnostics(). Tiles with no value stay grey and unlabelled. This plot ignores colour, size, show_legend, show_outliers, outliers_factor and outliers_labels.

  • colour: The column of nacho_samples(object) that colours the points.

  • size: The point size, and the line width in the "NORM" plot.

  • show_legend: If FALSE, hide the colour legend.

  • show_outliers: If TRUE, draw the flagged samples as triangles in the accent colour: rust on a light background, amber on a dark one.

  • outliers_factor: The size of the flagged samples, relative to size.

  • outliers_labels: The column of nacho_samples(object) that labels the flagged samples, or NULL for no labels. Labels imply show_outliers = TRUE.

  • dark: If TRUE, draw the plot for a dark background.

Examples

autoplot(GSE74821, type = "BD")