Metabolomics training differential analysis

Use limma to test the effect of training across timepoints. The analysis is performed separately for male and female rats and combined into a single p-value using sum of logs.

Usage

metab_training_da(tissue)

Arguments

tissue

character, tissue abbreviation, one of MotrpacRatTraining6moData::TISSUE_ABBREV

Value

a data frame with one row per metabolite:

feature_ID

character, MoTrPAC feature identifier

dataset

character, the metabolomics platform in which the metabolite is detected

groups_tested_female

character, timepoints used to perform the F-test in females. Some tissues or assays are missing timepoints.

groups_tested_male

character, timepoints used to perform the F-test in males. Some tissues or assays are missing timepoints.

fscore_male

double, F-statistic for males

fscore_female

double, F-statistic for females

p_value_male

double, nominal p-value for males

p_value_female

double, nominal p-value for females

full_model

character, full model used in limma

reduced_model

character, representation of the reduced model, though not used by limma

p_value

double, combined male and female nominal p-value using the sum of logs

Examples

# Perform training differential analysis for metabolites in heart tissue
res = metab_training_da("HEART")