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
)
A DESeq2::DESeqTransform()
object - usually the variance
stabilized transformed data, which will be used to extract the expression values
A character vector, usually named, containing the genes which compose the gene signature
A DESeq2::DESeqResults()
object. If not provided, it can
be computed during the execution of the application
Numeric value between 0 and 1, the False Discovery Rate
Logical, whether to display only DE genes belonging to the pathway - defaults to FALSE
A named character vector, with the corresponding annotation across IDs
Character, title for the heatmap
Logical, whether to cluster rows - defaults to TRUE
Logical, whether to cluster column - defaults to FALSE. Recommended to be set to TRUE if de_only is also set to TRUE
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.
Logical, whether to perform mean centering on the expression values. Defaults to TRUE, as it improves the general readability of the heatmap
Logical, whether to perform row-based standardization of the expression values
A plot based on the pheatmap
function
# 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
)
} # }