comp.mort_score {MiMIR} | R Documentation |
comp.mort_score
Description
Function to compute the mortality score made by Deelen et al. on Nightingale metabolomics data-set.
Usage
comp.mort_score(dat, betas = mort_betas, quiet = FALSE)
Arguments
dat |
numeric data-frame with Nightingale-metabolomics |
betas |
data.frame containing the coefficients used for the regression of the mortality score |
quiet |
logical to suppress the messages in the console |
Details
This multivariate model predicts all-cause mortality at 5 or 10 years better than clinical variables normally associated with mortality. It is constituted of 14 metabolic features quantified by Nightingale Health. It was originally trained using a stepwise Cox regression analysis in a meta-analysis on 12 cohorts composed by 44,168 individuals.
Value
data-frame containing the value of the mortality score on the uploaded data-set
References
This function is constructed to be able to apply the mortality score as described in: Deelen,J. et al. (2019) A metabolic profile of all-cause mortality risk identified in an observational study of 44,168 individuals. Nature Communications, 10, 1-8, doi:10.1038/s41467-019-11311-9
See Also
prep_met_for_scores, mort_betas, comp.T2D_Ahola_Olli, comp.CVD_score
Examples
library(MiMIR)
#load the Nightignale metabolomics dataset
metabolic_measures <- synthetic_metabolic_dataset
#Prepare the metabolic features fo the mortality score
mortScore<-comp.mort_score(metabolic_measures,quiet=TRUE)