plot_imputation: Visualize imputation

Description Usage Arguments Value Examples

View source: R/plot_functions_QC.R

Description

plot_imputation generates density plots of all conditions for input objects, e.g. before and after imputation.

Usage

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Arguments

se

SummarizedExperiment, Data object, e.g. before imputation (output from normalize_vsn()).

...

Other SummarizedExperiment object(s), E.g. data object after imputation (output from impute()).

Value

Density plots of all conditions of all conditions for input objects, e.g. before and after imputation (generated by ggplot).

Examples

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# 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)

# Plot imputation
plot_imputation(filt, norm, imputed)

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