impute_TF: Impute Transferrin (TF)

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

Description

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

Usage

impute_TF(GlycA, Sex, Age, S.HDL.FC, Ace, Ala, SFA, His, Gln,
  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.
Sex	The study participant's sex. The coding should be 1 for males, 2 for females.
Age	The study participant's age in years. Measurements should be between 25–74 years old.
S.HDL.FC	NMR measurement for free cholesterol within small HDL particles. Measurements should be between 0.0674–0.168 mmol/L.
Ace	NMR measurement for acetate. Measurements should be between 0.029–1.32 mmol/L.
Ala	NMR measurement for alanine. Measurements should be between 0.274–0.557 mmol/L.
SFA	NMR measurement for saturated fatty acids. Measurements should be between 2.07–7.02 mmol/L.
His	NMR measurement for histidine. Measurements should be between 0.0446–0.0913 mmol/L.
Gln	NMR measurement for glutamine. Measurements should be between 0.331–1.36 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 TF measurements ranging between 1.39–4.38 mg/L or measurements standardised to the population if standardised = 'TRUE'.

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