Lipid set enrichment analysis (LSEA)
lsea( de.results, rank.by = c("logFC", "P.Value", "adj.P.Val"), min_size = 2, ... ) significant_lipidsets(enrich.results, p.cutoff = 0.05, size.cutoff = 2) plot_class_enrichment(de.results, significant.sets, measure = "logFC") plot_enrichment( de.results, significant.sets, annotation = c("class", "length", "unsat"), measure = "logFC" )
Statistic used to rank the lipid list. Default is
Minimum number of molecules in a set to be included in enrichment.
Extra parameters passed to
Significance threshold. Default is
Minimum number of lipids in a set tested for enrichment.
List of significantly changed lipid sets
Which measure to plot the distribution of: logFC, P.Value,
Adj.P.Val. Default is
Which lipid set collection to plot.
lsea returns enrichment results (data.frame) as returned from
The results also contain the following attributes:
de.results Original de.results input.
rank.by Measure used to rank lipid molecules.
sets Lipid sets tested, with their member molecules.
significant_lipidsets returns a list of character vectors of
significantly enriched sets for each contrast.
plot_enrichment returns a ggplot object.
significant_lipidsets: gets a list of significantly changed lipid sets
plot_enrichment: is usually used to look at log2 fold change
distribution of lipids in each class, chain length or unsaturation,
marking significantly enriched sets. It can also be used to plot
data(data_normalized) de_results <- de_analysis( data_normalized, HighFat_water - NormalDiet_water, measure = "Area" ) enrich_results <- lsea( de_results, rank.by = "logFC", min_size = 4, nperm = 1000 ) #> Warning: There are ties in the preranked stats (5.78% of the list). #> The order of those tied genes will be arbitrary, which may produce unexpected results. sig_lipidsets <- significant_lipidsets(enrich_results) plot_enrichment(de_results, sig_lipidsets, annotation="class") plot_enrichment(de_results, sig_lipidsets, annotation="length")