ggs_graph {GeneTonic}R Documentation

Construct a gene-geneset-graph

Description

Construct a gene-geneset-graph from the results of a functional enrichment analysis

Usage

ggs_graph(
  res_enrich,
  res_de,
  annotation_obj = NULL,
  n_gs = 15,
  gs_ids = NULL,
  prettify = TRUE,
  geneset_graph_color = "gold",
  genes_graph_colpal = NULL
)

Arguments

res_enrich

A data.frame object, storing the result of the functional enrichment analysis. See more in the main function, GeneTonic(), to check the formatting requirements (a minimal set of columns should be present).

res_de

A DESeqResults object.

annotation_obj

A data.frame object with the feature annotation information, with at least two columns, gene_id and gene_name.

n_gs

Integer value, corresponding to the maximal number of gene sets to be included

gs_ids

Character vector, containing a subset of gs_id as they are available in res_enrich. Lists the gene sets to be displayed.

prettify

Logical, controlling the aspect of the returned graph object. If TRUE (default value), different shapes of the nodes are returned, based on the node type

geneset_graph_color

Character value, specifying which color should be used for the fill of the shapes related to the gene sets.

genes_graph_colpal

A vector of colors, also provided with their hex string, to be used as a palette for coloring the gene nodes. If unspecified, defaults to a color ramp palette interpolating from blue through yellow to red.

Value

An igraph object to be further manipulated or processed/plotted (e.g. via igraph::plot.igraph() or visNetwork::visIgraph())

Examples


library("macrophage")
library("DESeq2")
library("org.Hs.eg.db")
library("AnnotationDbi")

# dds object
data("gse", package = "macrophage")
dds_macrophage <- DESeqDataSet(gse, design = ~line + condition)
rownames(dds_macrophage) <- substr(rownames(dds_macrophage), 1, 15)
dds_macrophage <- estimateSizeFactors(dds_macrophage)

# annotation object
anno_df <- data.frame(
  gene_id = rownames(dds_macrophage),
  gene_name = mapIds(org.Hs.eg.db,
                     keys = rownames(dds_macrophage),
                     column = "SYMBOL",
                     keytype = "ENSEMBL"),
  stringsAsFactors = FALSE,
  row.names = rownames(dds_macrophage)
)

# res object
data(res_de_macrophage, package = "GeneTonic")
res_de <- res_macrophage_IFNg_vs_naive

# res_enrich object
data(res_enrich_macrophage, package = "GeneTonic")
res_enrich <- shake_topGOtableResult(topgoDE_macrophage_IFNg_vs_naive)
res_enrich <- get_aggrscores(res_enrich, res_de, anno_df)

ggs <- ggs_graph(res_enrich,
                 res_de,
                 anno_df
                )

ggs

#' # could be viewed interactively with
# library(visNetwork)
# library(magrittr)
# ggs %>%
#   visIgraph() %>%
#   visOptions(highlightNearest = list(enabled = TRUE,
#                                      degree = 1,
#                                      hover = TRUE),
#             nodesIdSelection = TRUE)
[Package GeneTonic version 0.99.6 Index]