plot_gsea {DEP} | R Documentation

## Plot enriched Gene Sets

### Description

`plot_gsea` plots enriched gene sets from Gene Set Enrichment Analysis.

### Usage

    plot_gsea(gsea_results, number = 10, alpha = 0.05, contrasts = NULL,
      databases = NULL, nrow = 1, term_size = 8)

### Arguments

`gsea_results` | Data.frame, Gene Set Enrichment Analysis results object. (output from `test_gsea()`).
`number` | Numeric(1), Sets the number of enriched terms per contrast to be plotted.
`alpha` | Numeric(1), Sets the threshold for the adjusted P value.
`contrasts` | Character, Specifies the contrast(s) to plot. If 'NULL' all contrasts will be plotted.
`databases` | Character, Specifies the database(s) to plot. If 'NULL' all databases will be plotted.
`nrow` | Numeric(1), Sets the number of rows for the plot.
`term_size` | Numeric(1), Sets the text size of the terms.

### Value

A barplot of the enriched terms (generated by `ggplot`).

### Examples

    # Load example
    data <- UbiLength
    data <- data[data$Reverse != "+" & data$Potential.contaminant != "+",]
    data_unique <- make_unique(data, "Gene.names", "Protein.IDs", delim = ";")

    # Make SummarizedExperiment
    columns <- grep("LFQ.", colnames(data_unique))
    exp_design <- UbiLength_ExpDesign
    se <- make_se(data_unique, columns, exp_design)

    # Filter, normalize and impute missing values
    filt <- filter_missval(se, thr = 0)
    norm <- normalize_vsn(filt)
    imputed <- impute(norm, fun = "MinProb", q = 0.01)

    # Test for differentially expressed proteins
    diff <- diff <- test_diff(imputed, "control", "Ctrl")
    dep <- add_rejections(diff, alpha = 0.05, lfc = 1)

    ## Not run:

    # Test enrichments
    gsea_results <- test_gsea(dep)
    plot_gsea(gsea_results)

    ## End(Not run)

[Package DEP version 1.9.0 Index]