plot_dist {DEP} | R Documentation |
plot_dist
generates a distance matrix heatmap using the Gower's distance.
plot_dist(dep, significant = TRUE, pal = "YlOrRd", pal_rev = TRUE, indicate = NULL, font_size = 12, plot = TRUE, ...)
dep |
SummarizedExperiment,
Data object for which differentially enriched proteins are annotated
(output from |
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 |
... |
Additional arguments for Heatmap function as depicted in
|
A heatmap plot (generated by Heatmap
)
# 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)