| plot_missval {DEP} | R Documentation |
plot_missval generates a heatmap of proteins
with missing values to discover whether values are missing by random or not.
plot_missval(se)
se |
SummarizedExperiment, Data object with missing values. |
A heatmap indicating whether values are missing (0) or not (1)
(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)
# Plot missing values heatmap
plot_missval(filt)