Analysis tables and plots of expression values
analyze_expressions.Rd
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
Examples
library(dplyr, warn.conflicts = FALSE)
library(tidyproteomics)
hela_proteins %>%
expression(knockdown/control) %>%
analyze_expressions(log2fc_min = 0.5, significance_column = "p_value")
#> ℹ .. expression::t_test testing knockdown / control
#> ✔ .. expression::t_test testing knockdown / control [3.4s]
#>
#> ℹ 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
#>