Volcano plot — plot_volcano • DEP2

plot_volcano generates a volcano plot for a specified contrast.

Usage

plot_volcano(
  object,
  contrast = get_contrast(object)[1],
  add_names = TRUE,
  dot_size = 2,
  label_size = 3,
  label_number = 10,
  label_trend = c("all", "up", "down", "none"),
  up_color = "#B2182B",
  down_color = "#2166AC",
  stable_color = "#BEBEBE",
  chooseTolabel = NULL,
  adjusted = FALSE,
  plot = TRUE,
  x_symmetry = TRUE,
  add_threshold_line = c("none", "intersect", "curve"),
  fcCutoff = 1,
  pCutoff = 0.05,
  curvature = 0.6,
  x0_fold = 2,
  breaks = NULL,
  highlight_PGs_with_few_peptides = F,
  peptide_1_color = "#A020F0",
  peptide_2_color = "#0000FF",
  peptide_column = "Peptides"
)

Arguments

object: SummarizedExperiment, Data object for which differentially enriched proteins are annotated (output from test_diff() or test_diff_deg() and add_rejections()).
contrast: Character(1), Specifies the contrast to plot.
add_names: Logical(1), Whether or not to plot names.
dot_size: numeric(1), the size of points.
label_size: numeric(1), Sets the size of name labels.
label_number: Integer(1). The number of plot name. Defalut NULL, label all significant names.
label_trend: Character(1). one of c("all","up","down"), plot all significant, up-regulated ones or down-regulated ones.
up_color: The color of upregulated points
down_color: The color of downregulated points
stable_color: The color of stable points
chooseTolabel: Character, Specify names to plot, no matter whether they are significant.
adjusted: Logical(1), Whether or not to use adjusted p values.
plot: Logical(1), If TRUE (default) the volcano plot is produced. Otherwise (if FALSE), the data which the volcano plot is based on are returned.
x_symmetry: Logical(1), if The X-axis is symmetric based on the 0.
add_threshold_line: Character(1), one of c("none", "intersect", "curve"). "intersect" draw a intersect cutoff line according fcCutoff and pCutoff. "curve" draw a curve cutoff line according curvature and x0_fold.
fcCutoff: numeric(1), Cutoff of L2FC.
pCutoff: numeric(1), Cutoff of p or p adjusted value
curvature: numeric(1), Curvature of curve cutoff line
x0_fold: numeric(1), The fold of x0 to Sigma.
breaks: Numeric vector, the position of x-axis label. eg: seq(-10,10,by = 5), c(-2, -1, 0, 1, 2).
highlight_PGs_with_few_peptides: logic(1), mark the proteins with few peptides by peptide_1_color and peptide_2_color. Require the peptide number variable(specified by peptide_column) in object.
peptide_1_color: The color of points with 1 peptide.
peptide_2_color: The color of points with 2 peptide.
peptide_column: Character(1), the varable column name storing the peptide number.

Value

A volcano plot (generated by ggplot)

Examples

# Load example
data(Silicosis_pg)
data <- Silicosis_pg
data_unique <- make_unique(data, "Gene.names", "Protein.IDs", delim = ";")

# Differential test
ecols <- grep("LFQ.", colnames(data_unique))
se <- make_se_parse(data_unique, ecols,mode = "delim")
filt <- filter_se(se, thr = 0, fraction = 0.4, filter_formula = ~ Reverse != "+" & Potential.contaminant!="+")
#> filter base on missing number is <= 0 in at least one condition.
#> filter base on missing number fraction < 0.4 in each row
#> filter base on giving formula 
norm <- normalize_vsn(filt)
#> vsn2: 8762 x 20 matrix (1 stratum). 
#> Please use 'meanSdPlot' to verify the fit.
imputed <- impute(norm, fun = "MinProb", q = 0.05)
#> Imputing along margin 2 (samples/columns).
#> [1] 0.3026531
diff <- test_diff(imputed, type = "control", control  = c("PBS"), fdr.type = "Storey's qvalue")
#> Tested contrasts: W10_vs_PBS, W2_vs_PBS, W4_vs_PBS, W6_vs_PBS, W9_vs_PBS
#> Storey's qvalue
dep <- add_rejections(diff, alpha = 0.01,lfc = 2)

plot_volcano(dep,contrast = "W4_vs_PBS")


dep <- add_rejections(diff, thresholdmethod = "curve")
plot_volcano(dep,contrast = "W4_vs_PBS",add_threshold_line= "curve")
#> add curve threshold line. Sigma = 0.402890639020025, x0 = 0.80578127804005, curvature = 0.6