ihw_pval_scatter: Plot p-value vs. IHW variable ranking

In bryancquach/omixjutsu: Utilities for omics analysis tasks

Plot p-value vs. IHW variable ranking

Description

Plots feature p-values vs. feature IHW variable rankings.

Usage

ihw_pval_scatter(
  ihw_data,
  truncate_y = F,
  point_color = "gray20",
  point_alpha = 0.5,
  point_size = 2
)

Arguments

ihw_data	An ihwResult object.
truncate_y	If 'TRUE', remove -log10 p-value outliers from the plot (exceed 1.5*IQR above the third quartile).
point_color	Scatterplot point fill color.
point_alpha	Scatterplot point fill color alpha value.
point_size	Scatterplot point size.

Details

This plot provides insight into how informative the selected IHW variable is in relation to the hypothesis being tested (e.g., differential gene expression). As IHW variable ranking increases (i.e., the rank gets larger) the p-values should trend smaller for more informative variables.

Value

A ggplot object.

See Also

Other ihw: ihw_diagnostic_plots(), ihw_partitioned_pval_weights(), ihw_pval_cdf(), ihw_pval_comparison(), ihw_pval_decision_boundary(), ihw_pval_ridges(), ihw_stratified_pval_hist()

bryancquach/omixjutsu documentation built on Jan. 29, 2023, 3:47 p.m.