impute_HP: Impute Haptoglobin (HP)

In InouyeLab/imputegp: Impute GlycA glycoproteins from serum NMR data in population studies

Description

Imputes the concentrations ofHP from serum NMR measurements in healthy population-based samples.

Usage

impute_HP(GlycA, LA, IDL.FC, SM, FAw3, HDL.TG, S.VLDL.CE, Age, Alb, Ile, Cit,
  VLDL.D, Leu, Val, L.VLDL.CE, Pyr, Lac, Gln, M.HDL.FC, XL.HDL.TG, XL.HDL.PL,
  His, Tyr, BMI, L.HDL.TG, PUFA, S.LDL.FC, range_check = TRUE,
  standardised = FALSE, na.omit = TRUE)

Arguments

GlycA	NMR measurement for glycoprotein acetyls. Measurements should be between 0.869–2.24 mmol/L.
LA	NMR measurement for 18:2 linoleic acid. Measurements should be between 0.449–5.15 mmol/L.
IDL.FC	NMR measurement for free cholesterol within IDL particles. Measurements should be between 0.0515–0.368 mmol/L.
SM	NMR measurement for sphingomyelins. Measurements should be between 0.103–0.733 mmol/L.
FAw3	NMR measurement for Omega-3 fatty acids. Measurements should be between 0.196–1.18 mmol/L.
HDL.TG	NMR measurement for triglycerides within all HDL particles. Measurements should be between 0.0698–0.315 mmol/L.
S.VLDL.CE	NMR measurement for cholesterol esters within small VLDL particles. Measurements should be between 0.000221–0.288 mmol/L.
Age	The study participant's age in years. Measurements should be between 25–74 years old.
Alb	NMR measurement for albumin. Measurements should have a signal area ranging between 0.0733–0.101.
Ile	NMR measurement for isoleucine. Measurements should be between 0.024–0.103 mmol/L.
Cit	NMR measurement for citrate. Measurements should be between 0.0739–0.186 mmol/L.
VLDL.D	NMR measurement for the mean diameter of VLDL particles. Measurements should be between 33–41 nm.
Leu	NMR measurement for leucine. Measurements should be between 0.0295–0.138 mmol/L.
Val	NMR measurement for valine. Measurements should be between 0.0728–0.297 mmol/L.
L.VLDL.CE	NMR measurement for cholesterol esters within large VLDL particles. Measurements should be between 0.00000152–0.161 mmol/L.
Pyr	NMR measurement for pyruvate. Measurements should be between 0.0512–0.179 mmol/L.
Lac	NMR measurement for lactate. Measurements should be between 0.69–4.93 mmol/L.
Gln	NMR measurement for glutamine. Measurements should be between 0.331–1.36 mmol/L.
M.HDL.FC	NMR measurement for free cholesterol within medium HDL particles. Measurements should be between 0.0208–0.145 mmol/L.
XL.HDL.TG	NMR measurement for triglycerides within very large HDL particles. Measurements should be between 0.000287–0.055 mmol/L.
XL.HDL.PL	NMR measurement for phospholipids within very large HDL particles. Measurements should be between 0.00176–0.639 mmol/L.
His	NMR measurement for histidine. Measurements should be between 0.0446–0.0913 mmol/L.
Tyr	NMR measurement for tyrosine. Measurements should be between 0.0279–0.124 mmol/L.
BMI	Body Mass Index. Measurements should be between 16.17–47.44 kg/m^2.
L.HDL.TG	NMR measurement for triglycerides within large HDL particles. Measurements should be between 0.000462–0.0993 mmol/L.
PUFA	NMR measurement for polyunsaturated fatty acids. Measurements should be between 2.29–6.62 mmol/L.
S.LDL.FC	NMR measurement for free cholesterol within small LDL particles. Measurements should be between 0.0215–0.133 mmol/L.
range_check	logical; if TRUE discard measurements that are not in the accepted range of values (see Details). If FALSE, no checking of input measurements or predicted concentrations will be performed.
standardised	logical; have measurements been standardised (i.e. using the scale function.)
na.omit	logical; should samples with missing values be omited? If FALSE missing values are set to the measurement's median in the model training dataset. Alternatively consider imputing missing values using impute.knn.

Details

The imputation models will only return a concentration where no input measurements were missing, and where all input measurements were within their acceptable predefined range of values. These correspond to their range of values in the training dataset. Similarly, the imputed measurement will be set to missing if the imputation model returns a concentration outside the range of values that were found in the training dataset.

Standardised measurements may also be used by setting standardised = 'TRUE', which is useful for cases where measurements must be adjusted for technical effects. In this case, all NMR measurements and BMI should be log transformed before scaling. Age and sex must also be standardised.

Value

A vector of HP measurements ranging between 0.14–3.95 mg/L or measurements standardised to the population if standardised = 'TRUE'.

InouyeLab/imputegp documentation built on May 23, 2019, 7:17 a.m.