gs_mds: Multi Dimensional Scaling plot for gene sets

In GeneTonic: Enjoy Analyzing And Integrating The Results From Differential Expression Analysis And Functional Enrichment Analysis

Description

Multi Dimensional Scaling plot for gene sets, extracted from a res_enrich object

Usage

gs_mds(
  res_enrich,
  res_de,
  annotation_obj,
  n_gs = nrow(res_enrich),
  gs_ids = NULL,
  similarity_measure = "kappa_matrix",
  mds_k = 2,
  mds_labels = 0,
  mds_colorby = "z_score",
  gs_labels = NULL,
  plot_title = NULL,
  return_data = FALSE
)

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 (from the top ranked ones). Defaults to the number of rows of res_enrich
gs_ids	Character vector, containing a subset of gs_id as they are available in res_enrich. Lists the gene sets to be included, additionally to the ones specified via n_gs. Defaults to NULL.
similarity_measure	Character, currently defaults to kappa_matrix, to specify how to compute the similarity measure between gene sets
mds_k	Integer value, number of dimensions to compute in the multi dimensional scaling procedure
mds_labels	Integer, defines the number of labels to be plotted on top of the scatter plot for the provided gene sets.
mds_colorby	Character specifying the column of res_enrich to be used for coloring the plotted gene sets. Defaults sensibly to z_score.
gs_labels	Character vector, containing a subset of gs_id as they are available in res_enrich. Lists the gene sets to be labeled.
plot_title	Character string, used as title for the plot. If left NULL, it defaults to a general description of the plot and of the DE contrast
return_data	Logical, whether the function should just return the data.frame of the MDS coordinates, related to the original res_enrich object. Defaults to FALSE.

Value

A ggplot object

See Also

create_kappa_matrix() is used to calculate the similarity between gene sets

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)

gs_mds(res_enrich,
       res_de,
       anno_df,
       n_gs = 200,
       mds_labels = 10)

GeneTonic documentation built on Nov. 8, 2020, 5:27 p.m.