MiMIR (version 1.5)

subset_samples_sd: subset_samples_sd

Description

Helper function that subsets the NH-metabolomics matrix to the samples with limited numbers of outliers

Usage

subset_samples_sd(x, MEAN, SD, quiet = FALSE)

Value

matrix with the samples with limited amount of outliers in the Nightingale-metabolomics dataset

Arguments

x

numeric data-frame with Nightingale-metabolomics

MEAN

numeric vector indicating the mean of the metabolites in x

SD

numeric vector indicating the standard deviations of the metabolites in x

quiet

logical to suppress the messages in the console

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, impute_miss, 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)
#Select the samples with low outliers
mat <- subset_samples_sd(x=metabolic_measures, Nmax=1)
}