plot.mGST {massiveGST}

Graphical rendering of the enrichment analysis.

Description

This function displays the enrichment analysis results both as a bar-plot and a network of gene-sets.

Usage

## S3 method for class 'mGST'
plot(x, 
  gene_sets = NULL, 
  order_by = "logit2NES", 
  top = 30, 
  eps = 0.25, 
  as.network = FALSE, 
  similarity_threshold = 1/3, 
  manipulation = FALSE, 
  autoResize = TRUE, 
  ...
)

Arguments

x

a data structure coming from the massiveGST function

gene_sets

a character vector of gene-sets; mandatory for the network display

order_by

a character string specifying whick should be the ordering in the bar-plot; must be one of "relevance", "NES", "logit2NES" (default), "p.value", "BH.value", and "bonferroni". These are the same options of summary.mGST

top

an integer value controlling how many gene-sets have to be displaued in the bar-plot; top = 30 (default)

as.network

a logical value to switch to a network display; as.network = FALSE (default)

similarity_threshold

a real value to cut the similarities between gene-stes below this value; similarity_threshold = 1/3 (default)

eps

a real value between 0.0 and 1.0 controlling the contribution of the Jaccard and overlap similaties to their convex combination; eps = 0.25 (default), see details.

manipulation

a logical value allowing to manipulate the network; manipulation = FALSE (default); see visOptions

autoResize

a logical value allowing to resize the network; resize = TRUE (default); see visOptions

...

other graphical parameters

Details

This function display the results of enrichment analysis both as a bar-plot and a network.

The network rendering is with the visNetwork package.

The similarity between the gene-set is computed a convex combination of the Jaccard and overlap similarities. See the reference for further details.

Value

In the case of network display, an object from the visNetwork package.

Author(s)

Stefano M. Pagnotta

References

Cerulo, Pagnotta (2022) doi:10.3390/e24050739

See Also

massiveGST, visNetwork, visOptions

Examples

library(massiveGST)

# get the gene profile
fname <- system.file("extdata", package="massiveGST")
fname <- file.path(fname, "pre_ranked_list.txt")
geneProfile <- get_geneProfile(fname)

# get the gene-sets
geneSets <- get_geneSets_from_msigdbr(category = "H", what = "gene_symbol")

# run the function
ans <- massiveGST(geneProfile, geneSets, alternative = "two.sided")

# to get the bar-plot
plot(cut_by_significance(ans, level_of_significance = 0.01))

# to get the network of the gene-sets
plot(cut_by_significance(ans, level_of_significance = 0.01), 
     gene_sets = geneSets, as.network = TRUE)