dat: numeric data-frame with Nightingale-metabolomics
betas: data.frame containing the coefficients used for the regression of the COVID-score
quiet: logical to suppress the messages in the console
Returns
data-frame containing the value of the COVID-score on the uploaded data-set
Details
Multivariate model predicting the risk of severe COVID-19 infection. It is based on 37 metabolic features and trained using LASSO regression on 52,573 samples from the UK-biobanks.
Examples
library(MiMIR)#load the Nightignale metabolomics datasetmetabolic_measures <- synthetic_metabolic_dataset
#Compute the mortality scoremortScore<-comp_covid_score(dat=metabolic_measures, quiet=TRUE)
References
This function is constructed to be able to apply the COVID-score as described in: Nightingale Health UK Biobank Initiative et al. (2021) Metabolic biomarker profiling for identification of susceptibility to severe pneumonia and COVID-19 in the general population. eLife, 10, e63033, doi:10.7554/eLife.63033