Usage
cmapHeatmap(x, reference.name, col.anno = NULL, row.anno = NULL, file.name = "heatmap", url.base = NULL, main = "Query gene scores", ColorRamp = colorRampPalette(c("#044381FF", "grey95", "grey95", "firebrick"))(100), col.col = c(down = "black", up = "grey"), row.col = c(correlated = "#1B9E77", anticorrelated = "#044381FF", over = "#1B9E77", under = "#044381FF"), order.by.score = TRUE, cluster.rows = TRUE, score.cap = c(-5, 5), ylab = "Significant datasets")
Arguments
x
numerical matrix with samples in rows and genes in columns.
reference.name
character, names of the reference cmap, used to construct the html image reference
col.anno
character vector with column annotations to be displayed as (horizontal) annotation bar above the heatmap. If not NULL, must contain one elment for each column of 'x'.
row.anno
character vector with row annotations to be displayed as (vertical) annotation to the right of the heatmap. If not NULL, must contain one element for each row of 'x'.
file.name
character, the path and filename (without suffix) to save the png file to
url.base
character, prefix for the html image reference
main
Character, main title of the plot
ColorRamp
vector of colors used for the heatmap, e.g. generated by a call to colorRampPalette
col.col
named vector with a color for each level of col.anno (e.g. c(up="firebrick", down="blue"))
row.col
named vector with a color for each level of row.anno (e.g. c(correlated="firebrick",anticorrelated="#044381FF"))
order.by.score
logical, should gene scores be reordered independently for each sample ?
cluster.rows
logical, perform hierarchical clustering on significant gene sets ?
score.cap
numerical vector of length two, specifying the limits of the color scale. Scores > max( score.cap) or < min(score.cap) will be set to score.cap. Default: c(-5,5)
ylab
character, y-axis label