Plot a heatmap of the gene signature on the data

Plot a heatmap for the selected gene signature on the provided data, with the possibility to compactly display also DE only genes

sig_heatmap(
  vst_data,
  my_signature,
  res_data = NULL,
  FDR = 0.05,
  de_only = FALSE,
  annovec,
  title = "",
  cluster_rows = TRUE,
  cluster_cols = FALSE,
  anno_colData = NULL,
  center_mean = TRUE,
  scale_row = FALSE
)

Arguments

vst_data: A DESeqTransform() object - usually the variance stabilized transformed data, which will be used to extract the expression values
my_signature: A character vector, usually named, containing the genes which compose the gene signature
res_data: A DESeqResults() object. If not provided, it can be computed during the execution of the application
FDR: Numeric value between 0 and 1, the False Discovery Rate
de_only: Logical, whether to display only DE genes belonging to the pathway - defaults to FALSE
annovec: A named character vector, with the corresponding annotation across IDs
title: Character, title for the heatmap
cluster_rows: Logical, whether to cluster rows - defaults to TRUE
cluster_cols: Logical, whether to cluster column - defaults to FALSE. Recommended to be set to TRUE if de_only is also set to TRUE
anno_colData: Character vector, specifying the elements of the colData information to be displayed as a decoration of the heatmap. Can be a vector of any length, as long as these names are included as colData. Defaults to NULL, which would plot no annotation on the samples.
center_mean: Logical, whether to perform mean centering on the expression values. Defaults to TRUE, as it improves the general readability of the heatmap
scale_row: Logical, whether to perform row-based standardization of the expression values

Value

A plot based on the pheatmap function

Examples

# with the well known airway package...
library("airway")
data("airway", package = "airway")
airway
#> class: RangedSummarizedExperiment 
#> dim: 63677 8 
#> metadata(1): ''
#> assays(1): counts
#> rownames(63677): ENSG00000000003 ENSG00000000005 ... ENSG00000273492
#>   ENSG00000273493
#> rowData names(10): gene_id gene_name ... seq_coord_system symbol
#> colnames(8): SRR1039508 SRR1039509 ... SRR1039520 SRR1039521
#> colData names(9): SampleName cell ... Sample BioSample
dds_airway <- DESeq2::DESeqDataSetFromMatrix(assay(airway),
  colData = colData(airway),
  design = ~ cell + dex
)
if (FALSE) { # \dontrun{
dds_airway <- DESeq2::DESeq(dds_airway)
res_airway <- DESeq2::results(dds_airway)
vst_airway <- DESeq2::vst(dds_airway)
library(org.Hs.eg.db)
annovec <- mapIds(org.Hs.eg.db, rownames(dds_airway), "ENTREZID", "ENSEMBL")
mysignatures <- read_gmt(
  "http://data.wikipathways.org/20190210/gmt/wikipathways-20190210-gmt-Homo_sapiens.gmt"
)
mysignature_name <- "Lung fibrosis%WikiPathways_20190210%WP3624%Homo sapiens"
library(pheatmap)
sig_heatmap(vst_airway,
  mysignatures[[mysignature_name]],
  res_data = res_airway,
  de_only = TRUE,
  annovec = annovec,
  title = mysignature_name,
  cluster_cols = TRUE
)
} # }