Write all relevant preprocessing visualizations to pdf

A wrapper around all the major visualization functions, used for visualizing data between major steps of data preprocessing. Saves all visualizations as PDFs with a set prefix on filenames.

Usage

visualizations(
  object,
  prefix,
  format = "pdf",
  perplexity = 30,
  merge = FALSE,
  remove_singles = FALSE,
  group = NULL,
  time = NULL,
  id = NULL,
  color = NULL,
  assay.type = NULL
)

Arguments

object: a SummarizedExperiment or MetaboSet object
prefix: character, a file path prefix added to the file paths
format: character, format in which the plots should be saved, DOES NOT support raster formats
perplexity: perplexity for t-SNE plots
merge: logical, whether the files should be merged to a single PDF, see Details
remove_singles: logical, whether to remove single plot files after merging. Only used if merge = TRUE
group: character, name of pheno data column containing the group labels
time: character, name of pheno data column containing timepoints
id: character, name of pheno data column containing subject identifiers
color: character, name of pheno data column used for coloring sample labels for dendrograms
assay.type: character, assay to be used in case of multiple assays

Value

None, the function is invoked for its plot-saving side effect.

Details

If merge is TRUE and format is pdf, then a file containing all the visualizations named prefix.pdf will be created. NOTE: on Windows this requires installation of pdftk (https://www.pdflabs.com/tools/pdftk-the-pdf-toolkit/) and on Linux you need to have pdfunite installed. On MacOS, no external software is needed. Note that at least on Windows, prefix should be a path from the root, so that the underlying system command will find the files. The type of visualizations to be saved depends on the type of object. Here is a comprehensive list of the visualizations:

Distribution of quality metrics and flags plot_quality
Boxplots of each sample in injection order plot_sample_boxplots
PCA scores plot of samples colored by injection order plot_pca
t-SNE plot of samples colored by injection order plot_tsne
If the object has over 60 samples, hexbin versions of the PCA and t- SNE plots above plot_pca_hexbin, plot_tsne_hexbin
Dendrogram of samples ordered by hierarchical clustering, sample labels colored by group if present plot_dendrogram
heat map of intersample distances, ordered by hierarchical clustering plot_sample_heatmap
If the object has QC samples:
- Density function of the intersample distances in both QCs and biological samples plot_dist_density
- Histograms of p-values from linear regression of features against injection order in both QCs and biological samples plot_p_histogram
If the object has a group column:
- PCA and tSNE plots with points shaped and colored by group plot_pca, plot_tsne
If the object has a time column:
- PCA and tSNE plots with points shaped and colored by time 'plot_pca, plot_tsne
- Dendrogram of samples ordered by hierarchical clustering, sample labels colored by time point plot_dendrogram
If the object has a group column OR a time column:
- Boxplots of samples ordered and colored by group and/or time plot_sample_boxplots
If the object has a group column AND a time column:
- PCA and tSNE plots with points shaped by group and colored by time plot_pca, plot_tsne
If the object has a time column AND a subject column:
- PCA and tSNE plots with arrows connecting the samples of each subject in time point order plot_pca_arrows, plot_tsne_arrows

Examples