manual_impute {DEP} | R Documentation

## Imputation by random draws from a manually defined distribution

### Description

`manual_impute` imputes missing values in a proteomics dataset by random draws from a manually defined distribution.

### Usage

    manual_impute(se, scale = 0.3, shift = 1.8)

### Arguments

`se` | SummarizedExperiment, Proteomics data (output from `make_se()` or `make_se_parse()`). It is adviced to first remove proteins with too many missing values using `filter_missval()` and normalize the data using `normalize_vsn()`.
`scale` | Numeric(1), Sets the width of the distribution relative to the standard deviation of the original distribution.
`shift` | Numeric(1), Sets the left-shift of the distribution (in standard deviations) from the median of the original distribution.

### Value

An imputed SummarizedExperiment object.

### 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 and normalize
    filt <- filter_missval(se, thr = 0)
    norm <- normalize_vsn(filt)

    # Impute missing values manually
    imputed_manual <- impute(norm, fun = "man", shift = 1.8, scale = 0.3)

[Package DEP version 1.6.1 Index]