plot_dist: Plot Gower's distance matrix

In arnesmits/DEP: Differential Enrichment analysis of Proteomics data

Description

plot_dist generates a distance matrix heatmap using the Gower's distance.

Usage

plot_dist(dep, significant = TRUE, pal = "YlOrRd", pal_rev = TRUE,
  indicate = NULL, font_size = 12, plot = TRUE, ...)

Arguments

dep	SummarizedExperiment, Data object for which differentially enriched proteins are annotated (output from test_diff() and add_rejections()).
significant	Logical(1), Whether or not to filter for significant proteins.
pal	Character(1), Sets the color panel (from RColorBrewer).
pal_rev	Logical(1), Whether or not to invert the color palette.
indicate	Character, Sets additional annotation on the top of the heatmap based on columns from the experimental design (colData).
font_size	Integer(1), Sets the size of the labels.
plot	Logical(1), If TRUE (default) the distance matrix plot is produced. Otherwise (if FALSE), the data which the distance matrix plot is based on are returned.
...	Additional arguments for Heatmap function as depicted in Heatmap

Value

A heatmap plot (generated by Heatmap)

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 correlation matrix
plot_dist(dep)

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