plot_imputation {DEP} | R Documentation

## Visualize imputation

### Description

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

### Usage

    plot_imputation(se, ...)

### 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

    # 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)

[Package DEP version 1.2.0 Index]