jaccard_heatmap {bulkAnalyseR}

Create a heatmap of the Jaccard similarity index (JSI) between samples of an experiment

Description

This function creates a JSI heatmap between all samples in the expression matrix using the specified number of most abundant genes as input. Metadata columns are used as annotations.

Usage

jaccard_heatmap(
  expression.matrix,
  metadata,
  top.annotation.ids = NULL,
  n.abundant = NULL,
  show.values = TRUE,
  show.row.column.names = TRUE
)

Arguments

expression.matrix

the expression matrix; rows correspond to genes and columns correspond to samples; usually preprocessed by preprocessExpressionMatrix; a list (of the same length as modality) can be provided if #' length(modality) > 1

metadata

a data frame containing metadata for the samples contained in the expression.matrix; must contain at minimum two columns: the first column must contain the column names of the expression.matrix, while the last column is assumed to contain the experimental conditions that will be tested for differential expression; a list (of the same length as modality) can be provided if #' length(modality) > 1

top.annotation.ids

a vector of column indices denoting which columns of the metadata should become heatmap annotations

n.abundant

number of most abundant genes to use for the JSI calculation

show.values

whether to show the JSI values within the heatmap squares

show.row.column.names

whether to show the row and column names below the heatmap; default is TRUE

Value

The JSI heatmap as detailed in the ComplexHeatmap package.

Examples

expression.matrix.preproc <- as.matrix(read.csv(
  system.file("extdata", "expression_matrix_preprocessed.csv", package = "bulkAnalyseR"), 
  row.names = 1
))[1:500,]

metadata <- data.frame(
  srr = colnames(expression.matrix.preproc), 
  timepoint = rep(c("0h", "12h", "36h"), each = 2)
)
print(jaccard_heatmap(expression.matrix.preproc, metadata, n.abundant = 100))