QCprep {MiMIR}

QCprep

Description

Helper function to pre-process the Nightingale Health metabolomics data-set before applying the MetaboAge score by van den Akker et al.

Usage

QCprep(mat, PARAM_metaboAge, quiet = TRUE, Nmax_zero = 1, Nmax_miss = 1)

Arguments

mat

numeric data-frame NH-metabolomics matrix.

PARAM_metaboAge

list containing all the parameters to compute the metaboAge (metabolic features list,BBMRI-nl means and SDs of the metabolic features, and coefficients)

quiet

logical to suppress the messages in the console

Nmax_zero

numberic value indicating the maximum number of zeros allowed per sample (Number suggested=1)

Nmax_miss

numberic value indicating the maximum number of missing values allowed per sample (Number suggested=1)

Value

Nightingale-metabolomics data-frame after pre-processing (checked for zeros, missing values, samples>5SD from the BBMRI-mean, imputing the missing values and z-scaled)

References

This function is constructed to be able to follow the pre-processing steps 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/CIRCULATIONAHA.114.013116

See Also

apply.fit

Examples

library(MiMIR)

#load the Nightignale metabolomics dataset
metabolic_measures <- synthetic_metabolic_dataset

#Pre-process the metabolic features
prepped_met<-QCprep(as.matrix(metabolic_measures[,metabolites_subsets$MET63]), PARAM_metaboAge)