Helper plot function for identification of outliers

Beeswarm plot of the percentage of detected genes per sample, with the outlier cutoffs drawn in. Used in the bulk DGE pre-processing report.

Usage

plot_preprocessing_outliers(samples, group_col, min_perc, max_perc)

Arguments

samples

data.table with sample information with perc_detected_genes and a column specifying the cohort.

group_col

String specifying the column with cohort information

min_perc

Numeric. Lower cutoff to identify outliers.

max_perc

Numeric. Upper cutoff to identify outliers

Value

ggplot object, i.e., beeswarm plot with outlier indication

Examples

# percentage of detected genes with the outlier cutoffs drawn in
syn <- synthetic_bulk_cor_matrix()
samples <- data.table::data.table(
  cohort = rep(c("case", "control"), each = 50),
  perc_detected_genes = colMeans(syn$counts > 0) * 100
)
plot_preprocessing_outliers(
  samples,
  group_col = "cohort",
  min_perc = 60,
  max_perc = 95
)