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Imputation by the truncated k-nearest neighbors algorithm

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

Apply imputation to the dataset by the truncated k-nearest neighbors algorithm (Shah et al. 2017) .

Usage

impute.knn_trunc(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

Shah JS, Rai SN, DeFilippis AP, Hill BG, Bhatnagar A, Brock GN (2017). “Distribution Based Nearest Neighbor Imputation for Truncated High Dimensional Data with Applications to Pre-Clinical and Clinical Metabolomics Studies.” BMC bioinformatics, 18, 114. doi:10.1186/s12859-017-1547-6 .