subset_samples_sd {MiMIR} | R Documentation |
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)
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 |
Value
matrix with the samples with limited amount of outliers in the Nightingale-metabolomics dataset
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
## Not run:
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)
## End(Not run)