View source: R/DEsummaryFuns.R
expression_heatmap | R Documentation |
This function creates a heatmap to visualise an expression matrix
expression_heatmap( expression.matrix.subset, top.annotation.ids = NULL, metadata, type = c("Z-score", "Log2 Expression", "Expression"), show.column.names = TRUE )
expression.matrix.subset |
a subset of rows from the expression matrix; rows correspond to genes and columns correspond to samples |
top.annotation.ids |
a vector of column indices denoting which columns of the metadata should become heatmap annotations |
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 #' |
type |
type of rescaling; one of "Expression" (defautl, does nothing), "Log2 Expression" (returns log2(x + 1) for every value), "Mean Scaled" (each row is scaled by its average), "Z-score" (each row is centered and scaled to mean = 0 and sd = 1) |
show.column.names |
whether to show the column names below the heatmap; default is TRUE |
The heatmap as detailed in the ComplexHeatmap package.
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(expression_heatmap(head(expression.matrix.preproc), NULL, metadata))
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