impute_miss function

impute_miss

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

impute_miss(x)

Arguments

• x: numeric data-frame with Nightingale-metabolomics

Returns

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

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

Examples

## Not run:

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)
## End(Not run)

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