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analyze_expressions() is a GGplot2 implementation for plotting the expression differences as foldchange ~ statistical significance. See also plot_proportion(). This function can take either a tidyproteomics data object or a table with the required headers.

Usage

analyze_expressions(
  data = NULL,
  log2fc_min = 1,
  log2fc_column = "log2_foldchange",
  significance_max = 0.05,
  significance_column = "adj_p_value",
  labels_column = NULL,
  show_pannels = TRUE,
  show_lines = TRUE,
  show_fc_scale = TRUE,
  show_title = TRUE,
  show_pval_1 = TRUE,
  point_size = NULL,
  color_positive = "dodgerblue",
  color_negative = "firebrick1",
  height = 5,
  width = 8
)

Arguments

log2fc_min

a numeric defining the minimum log2 foldchange to highlight.

log2fc_column

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

significance_max

a numeric defining the maximum statistical significance to highlight.

significance_column

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

labels_column

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

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.

show_title

input FALSE, TRUE for an auto-generated title or any charcter string.

show_pval_1

a boolean for showing expressions with pvalue == 1.

point_size

a character reference to a numerical value in the expression table

color_positive

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

color_negative

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

height

a numeric

width

a numeric

Value

a tidyproteomics data object

Examples

library(dplyr, warn.conflicts = FALSE)
library(tidyproteomics)
hela_proteins %>%
   expression(knockdown/control) %>%
   analyze_expressions(log2fc_min = 0.5, significance_column = "p_value")
#>  .. expression::t_test testing knockdown / control
#>  .. expression::t_test testing knockdown / control [3.4s]
#> 
#>  Saved plot_volcano.png
#> 
#> ── Quantitative Proteomics Data Object ──
#> 
#> Origin          ProteomeDiscoverer 
#>                 proteins (11.40 MB) 
#> Composition     6 files 
#>                 2 samples (control, knockdown) 
#> Quantitation    7055 proteins 
#>                 4 log10 dynamic range 
#>                 28.8% missing values 
#>  *imputed        
#> Accounting      (4) num_peptides num_psms num_unique_peptides imputed 
#> Annotations     (9) description biological_process cellular_component molecular_function
#>                 gene_id_entrez gene_name wiki_pathway reactome_pathway
#>                 gene_id_ensemble 
#> Analyses        (1) 
#>                 knockdown/control -> expression  
#>