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plot_proportion() is a GGplot2 implementation for plotting the expression differences as foldchange ~ scaled abundance. This allows for the visualization of selected proteins See also plot_volcano(). This function can take either a tidyproteomics data object or a table with the required headers.

Usage

plot_proportion(
  data = NULL,
  ...,
  log2fc_column = "log2_foldchange",
  log2fc_min = 2,
  significance_column = "adj_p_value",
  significance_max = 0.05,
  proportion_column = "proportional_expression",
  proportion_min = 0.01,
  labels_column = NULL,
  label_significance = TRUE,
  show_pannels = FALSE,
  show_lines = TRUE,
  show_fc_scale = TRUE,
  point_size = NULL,
  color_positive = "dodgerblue",
  color_negative = "firebrick1",
  destination = "plot",
  height = 5,
  width = 8
)

Arguments

data

a tidyproteomics data object

...

two sample comparison

log2fc_column

a character defining the column name of the log2 foldchange values.

log2fc_min

a numeric defining the minimum log2 foldchange to highlight.

significance_column

a character defining the column name of the statistical significance values.

significance_max

a numeric defining the maximum statistical significance to highlight.

proportion_column

a character defining the column name of the proportional expression values.

proportion_min

a numeric defining the minimum proportional expression to highlight.

labels_column

a character defining the column name of the column for labeling.

label_significance

a boolean for labeling values below the significance threshold.

show_pannels

a boolean for showing colored up/down expression panels.

show_lines

a boolean for showing threshold lines.

show_fc_scale

a boolean for showing the secondary foldchange scale.

point_size

a numeric for shanging the point size.

color_positive

a character defining the color for positive (up) expression.

color_negative

a character defining the color for negative (down) expression.

destination

a character string

height

a numeric

width

a numeric

Value

a ggplot2 object

Examples

library(dplyr, warn.conflicts = FALSE)
library(tidyproteomics)
hela_proteins %>%
   expression(knockdown/control) %>%
   plot_proportion(knockdown/control, log2fc_min = 0.5, significance_column = 'p_value')
#>  .. expression::t_test testing knockdown / control
#>  .. expression::t_test testing knockdown / control [3.7s]
#> 
#>  proportional_expression appears to sum to 1 adjusting values to 100(%)
#> Warning: ggrepel: 381 unlabeled data points (too many overlaps). Consider increasing max.overlaps


# generates the same out come
# hela_proteins %>%
#    expression(knockdown/control) %>%
#    export_analysis(knockdown/control, .analysis = 'expression) %>%
#    plot_proportion(log2fc_min = 0.5, significance_column = 'p_value')

# display the gene name instead
hela_proteins %>%
   expression(knockdown/control) %>%
   plot_proportion(knockdown/control, log2fc_min = 0.5, significance_column = 'p_value', labels_column = "gene_name")
#>  .. expression::t_test testing knockdown / control
#>  .. expression::t_test testing knockdown / control [3.2s]
#> 
#>  proportional_expression appears to sum to 1 adjusting values to 100(%)
#> Warning: Removed 13 rows containing missing values or values outside the scale range
#> (`geom_text_repel()`).
#> Warning: ggrepel: 367 unlabeled data points (too many overlaps). Consider increasing max.overlaps