lsea {lipidr} | R Documentation

## Lipid set enrichment analysis (LSEA)

### Description

Lipid set enrichment analysis (LSEA)

### Usage

    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"
    )

### Arguments

`de.results` | Output of `de_analysis()`.
`rank.by` | Statistic used to rank the lipid list. Default is `logFC`.
`min_size` | Minimum number of molecules in a set to be included in enrichment.
`...` | Extra parameters passed to `fgsea::fgsea()`.
`enrich.results` | Output of `lsea()`.
`p.cutoff` | Significance threshold. Default is `0.05`.
`size.cutoff` | Minimum number of lipids in a set tested for enrichment. Default is `2`.
`significant.sets` | List of significantly changed lipid sets (output of `significant_lipidsets()`).
`measure` | Which measure to plot the distribution of: logFC, P.Value, Adj.P.Val. Default is `logFC`.
`annotation` | Which lipid set collection to plot.

### Value

`lsea` returns enrichment results (data.frame) as returned from `fgsea::fgsea()`. 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.

### Functions

- `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 `P.Value` or `Adj.P.Val`.

### Examples

    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
    )
    sig_lipidsets <- significant_lipidsets(enrich_results)
    plot_enrichment(de_results, sig_lipidsets, annotation="class")
    plot_enrichment(de_results, sig_lipidsets, annotation="length")

[Package lipidr version 2.6.0 Index]