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Imputation by the k-nearest neighbors algorithm

Source: R/imputations.R
impute.knn_seq.Rd

Apply imputation to the dataset by the sequential k-nearest neighbors algorithm (Kim et al. 2004) .

Usage

impute.knn_seq(dataSet, reportImputing = FALSE, k = 10)

Arguments

dataSet

The 2d dataset of experimental values.

reportImputing

A boolean (default = FALSE) specifying whether to provide a shadow data frame with imputed data labels, where 1 indicates the corresponding entries have been imputed, and 0 indicates otherwise. Alters the return structure.

k

An integer (default = 10) indicating the number of neighbors to be used in the imputation.

Value

  • If reportImputing = FALSE, the function returns the imputed 2d dataframe.

  • If reportImputing = TRUE, the function returns a list of the imputed 2d dataframe and a shadow matrix showing which proteins by replicate were imputed.

References

Kim K, Kim B, Yi G (2004). “Reuse of Imputed Data in Microarray Analysis Increases Imputation Efficiency.” BMC bioinformatics, 5, 160. doi:10.1186/1471-2105-5-160 .