plot_cond_freq: Plot frequency of significant conditions per protein

In arnesmits/DEP: Differential Enrichment analysis of Proteomics data

Description

plot_cond_freq generates a histogram of the number of significant conditions per protein.

Usage

plot_cond_freq(dep, plot = TRUE)

Arguments

dep	SummarizedExperiment, Data object for which differentially enriched proteins are annotated (output from test_diff() and add_rejections()).
plot	Logical(1), If TRUE (default) the histogram is produced. Otherwise (if FALSE), the data which the histogram is based on are returned.

Value

A histogram (generated by ggplot)

Examples

# Load example
data <- UbiLength
data <- data[data$Reverse != "+" & data$Potential.contaminant != "+",]
data_unique <- make_unique(data, "Gene.names", "Protein.IDs", delim = ";")

# Make SummarizedExperiment
columns <- grep("LFQ.", colnames(data_unique))
exp_design <- UbiLength_ExpDesign
se <- make_se(data_unique, columns, exp_design)

# Filter, normalize and impute missing values
filt <- filter_missval(se, thr = 0)
norm <- normalize_vsn(filt)
imputed <- impute(norm, fun = "MinProb", q = 0.01)

# Test for differentially expressed proteins
diff <- test_diff(imputed, "control", "Ctrl")
dep <- add_rejections(diff, alpha = 0.05, lfc = 1)

# Plot frequency of significant conditions
plot_cond_freq(dep)

arnesmits/DEP documentation built on Aug. 7, 2019, 10:44 a.m.