compute_models_with_limmaR Documentation

Compute lipid-specific regression models

Description

Use this function to computing multiple regression models that can be directly supplied to the visualization functions of the 'lipidomeR'.

Usage

compute_models_with_limma(
  x,
  dependent.variables,
  independent.variables,
  random.effect = NULL,
  formula = NULL,
  F.test = FALSE,
  print.table1 = FALSE,
  scale.dependent.variables = TRUE,
  scale.independent.variables = FALSE,
  verbose = TRUE
)

Arguments

x

(Required) data matrix.

dependent.variables

(Required) vector of names of dependent variables. These should be the names of the lipids.

independent.variables

(Required) vector of names of the independent variables. These should be the names of the variables defining the experiment design.

random.effect

(Optional) name of a single variable specifying the random effect for a random-effects model. For instance, ID specifies a random effect as in limma::duplicateCorrelation( ..., block = x$'ID' ).

formula

(Optional) character string of model formula in the format accepted by the function model.matrix and starting with ~. Variables mentioned in the formula should be included in the independent.variables argument. For instance, Group * Treatment.

F.test

(Optional) TRUE or FALSE: Should an F-test for analysis of variance (ANOVA) or analysis of covariance (ANCOVA) be computed?

print.table1

(Optional) TRUE or FALSE: Should a summary table of the independent variables be printed?

scale.dependent.variables

(Optional) TRUE or FALSE: Should dependent variables be scaled to zero-mean and unit-variance prior to model fitting?

scale.independent.variables

(Optional) TRUE or FALSE: Should independent variables be scaled to zero-mean and unit-variance prior to model fitting?

verbose

(Optional) TRUE or FALSE: Print messages from the model fitting?

Value

List of regression results the that can be directly supplied as an argument to the function heatmap_lipidome_from_limma and other visualization functions of the lipidomeR.

See Also

heatmap_lipidome_from_limma for visualizing the output of this function.