Metabolomics-Based Models for Imputing Risk
apply.scale
multi_hist
activateButtn
apply.fit
apply.fit_surro
binarize_all_pheno
BMI_LDL_eGFR
calculate_surrogate_scores
calib_data_frame
calibration_surro
comp.CVD_score
comp.mort_score
comp.T2D_Ahola_Olli
comp_covid_score
cor_assoc
Helper function to compute MetaboWASs
find_BBMRI_names
get.p
get.s
getECE
helper function to calculate the MCE of the calibrations
getvol
hist_plots
hist_plots_mortality
impute_miss
is.sym
kapmeier_scores
withSpinner
loading_spin
LOBOV_accuracies
MetaboWAS
model_coeff_heat
MOLEPI_LCBC_header
multi_hist
NA_message
pheno_barplots
Function that plots the Platt Calibrations using plotly
plattCalibration
plot_corply
plot_na_heatmap
plotly_NA_message
predictions_surrogates
prep_data_COVID_score
prep_met_for_scores
QCprep
QCprep_surrogates
rendertable
report.dim
resort.on.p
resort.on.s
roc_surro
roc_surro_subplots
scatterplot_predictions
startMiMIR
subset_metabolites_overlap
subset_samples_miss
subset_samples_sd
subset_samples_sd_surrogates
subset_samples_miss
ttest_scores
ttest_surrogates
Provides an intuitive framework for ad-hoc statistical analysis of 1H-NMR metabolomics by Nightingale Health. It allows to easily explore new metabolomics measurements assayed by Nightingale Health, comparing the distributions with a large Consortium (BBMRI-nl); project previously published metabolic scores [<doi:10.1016/j.ebiom.2021.103764>, <doi:10.1161/CIRCGEN.119.002610>, <doi:10.1038/s41467-019-11311-9>, <doi:10.7554/eLife.63033>, <doi:10.1161/CIRCULATIONAHA.114.013116>, <doi:10.1007/s00125-019-05001-w>]; and calibrate the metabolic surrogate values to a desired dataset.