plot_dist: Plot Gower's distance matrix

Description Usage Arguments Value Examples

View source: R/plot_functions_explore.R

Description

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

Usage

1
2
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

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
19
20
21
# 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)

squirrelandr/DEP documentation built on May 7, 2019, 9:31 a.m.