Description Usage Arguments Value Examples
View source: R/plot_functions_QC.R
plot_missval
generates a heatmap of proteins
with missing values to discover whether values are missing by random or not.
1 | plot_missval(se)
|
se |
SummarizedExperiment, Data object with missing values. |
A heatmap indicating whether values are missing (0) or not (1)
(generated by Heatmap
).
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | # 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)
|
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