MiMIR (version 1.5)

impute_miss: impute_miss

Description

Helper function that subsets the NH-metabolomics matrix to the samples with less than Nmax zeros

Usage

impute_miss(x)

Value

matrix of the Nightingale-metabolomics dataset with missing values imputed to zero

Arguments

x

numeric data-frame with Nightingale-metabolomics

Details

Function created that subsets the NH-metabolomics matrix samples to the ones for which the metabolites included in MetaboAge for which the log of the metabolic concentrations are not more than 5SD away from their mean

References

This function is constructed to be able to apply the metaboAge as described in: van den Akker Erik B. et al. (2020) Metabolic Age Based on the BBMRI-NL 1H-NMR Metabolomics Repository as Biomarker of Age-related Disease. Circulation: Genomic and Precision Medicine, 13, 541-547, doi:10.1161/CIRCGEN.119.002610

See Also

QCprep, apply.fit, subset_metabolites_overlap, subset_samples_miss, subset_samples_zero, subset_samples_sd, apply.scale, and report.dim

Examples

if (FALSE) {
library(MiMIR)

#load the Nightignale metabolomics dataset
metabolic_measures <- read.csv("Nightingale_file_path",header = TRUE, row.names = 1)
#Imputing missing values
mat <- impute_miss(metabolic_measures)
}