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Linear models

Source: R/stats.R
perform_lm.Rd

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

Usage

perform_lm(object, formula_char, all_features = FALSE, assay.type = NULL, ...)

Arguments

object

a SummarizedExperiment or 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?

assay.type

character, assay to be used in case of multiple assays

...

additional parameters passed to lm

Value

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

Details

The linear model is fit on combined_data(object). Thus, column names in pheno data 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.

See also

lm

Examples

data(example_set)
# 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")
#> INFO [2025-06-23 22:37:26] Starting linear regression.
#> INFO [2025-06-23 22:37:26] Linear regression performed.