impute {QFeatures} | R Documentation

## Quantitative proteomics data imputation

### Description

The `impute` method performs data imputation on `QFeatures` and `SummarizedExperiment` instance using a variety of methods.

Users should proceed with care when imputing data and take precautions to assure that the imputation produce valid results, in particular with naive imputations such as replacing missing values with 0.

See `MsCoreUtils::impute_matrix()` for details on the different imputation methods available and strategies.

### Usage

    impute

    ## S4 method for signature 'SummarizedExperiment'
    impute(object, method, ...)

    ## S4 method for signature 'QFeatures'
    impute(object, method, ..., i)

### Arguments

`object` | A `SummarizedExperiment` or `QFeatures` object with missing values to be imputed.
`method` | `character(1)` defining the imputation method. See `imputeMethods()` for available ones. See `MsCoreUtils::impute_matrix()` for details.
`...` | Additional parameters passed to the inner imputation function. See `MsCoreUtils::impute_matrix()` for details.
`i` | Defines which element of the `QFeatures` instance to impute. If missing, all assays will be imputed.

### Format

An object of class `standardGeneric` of length 1.

### Examples

    MsCoreUtils::imputeMethods()

    data(se_na2)
    ## table of missing values along the rows (proteins)
    table(rowData(se_na2)$nNA)
    ## table of missing values along the columns (samples)
    colData(se_na2)$nNA

    ## non-random missing values
    notna <- which(!rowData(se_na2)$randna)
    length(notna)
    notna

    impute(se_na2, method = "min")

    if (require("imputeLCMD")) {
      impute(se_na2, method = "QRILC")
      impute(se_na2, method = "MinDet")
    }

    if (require("norm"))
      impute(se_na2, method = "MLE")

    impute(se_na2, method = "mixed",
           randna = rowData(se_na2)$randna,
           mar = "knn", mnar = "QRILC")

    ## neighbour averaging
    x <- se_na2[1:4, 1:6]
    assay(x)[1, 1] <- NA ## min value
    assay(x)[2, 3] <- NA ## average
    assay(x)[3, 1:2] <- NA ## min value and average
    ## 4th row: no imputation
    assay(x)

    assay(impute(x, "nbavg"))

[Package QFeatures version 1.2.0 Index]