plot_gsea {DEP} | R Documentation |
plot_gsea
plots enriched gene sets
from Gene Set Enrichment Analysis.
plot_gsea(gsea_results, number = 10, alpha = 0.05, contrasts = NULL, databases = NULL, nrow = 1, term_size = 8)
gsea_results |
Data.frame,
Gene Set Enrichment Analysis results object.
(output from |
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. |
A barplot of the enriched terms
(generated by ggplot
).
# 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)