MiMIR (version 1.5)

comp_covid_score: comp_covid_score

Description

Function to compute the COVID severity score made by Nightingale Health UK Biobank Initiative et al. on Nightingale metabolomics data-set.

Usage

comp_covid_score(dat, betas = MiMIR::covid_betas, quiet = FALSE)

Value

data-frame containing the value of the COVID-score on the uploaded data-set

Arguments

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

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.

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

See Also

prep_data_COVID_score, covid_betas, comp.mort_score

Examples

library(MiMIR)

#load the Nightignale metabolomics dataset
metabolic_measures <- synthetic_metabolic_dataset

#Compute the mortality score
mortScore<-comp_covid_score(dat=metabolic_measures, quiet=TRUE)