perform_lm: Linear models

In antonvsdata/amp: Smoothing Metabolomics Analyses

Description

Fits a linear model separately for each feature. Returns all relevant statistics.

Usage

perform_lm(object, formula_char, all_features = FALSE, ci_level = 0.95,
  ...)

Arguments

object	a MetaboSet object
formula_char	character, the formula to be used in the linear model (see Details)
all_features	should all features be included in FDR correction?
ci_level	the confidence level used in constructing the confidence intervals for regression coefficients
...	additional parameters passed to lm

Details

The linear model is fit on combined_data(object). Thus, column names in pData(object) can be specified. To make the formulas flexible, the word "Feature" must be used to signal the role of the features in the formula. "Feature" will be replaced by the actual Feature IDs during model fitting, see the example

Value

a data frame with one row per feature, with all the relevant statistics of the linear model as columns

See Also

lm

Examples

# A simple example without QC samples
# Features predicted by Group and Time
lm_results <- perform_lm(drop_qcs(example_set), formula_char = "Feature ~ Group + Time")

antonvsdata/amp documentation built on Jan. 8, 2020, 3:15 a.m.