Multi Dimensional Scaling plot for gene sets

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

gs_mds(
  res_enrich,
  res_de,
  annotation_obj,
  gtl = NULL,
  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.
gtl: A GeneTonic-list object, containing in its slots the arguments specified above: dds, res_de, res_enrich, and annotation_obj - the names of the list must be specified following the content they are expecting
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

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)
#> using counts and average transcript lengths from tximeta
rownames(dds_macrophage) <- substr(rownames(dds_macrophage), 1, 15)
dds_macrophage <- estimateSizeFactors(dds_macrophage)
#> using 'avgTxLength' from assays(dds), correcting for library size

# 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)
)
#> 'select()' returned 1:many mapping between keys and columns

# 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)
#> Found 500 gene sets in `topGOtableResult` object.
#> Converting for usage in GeneTonic...
res_enrich <- get_aggrscores(res_enrich, res_de, anno_df)

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

Multi Dimensional Scaling plot for gene sets

Arguments

Value

See also

Examples