Fast and easy visualisations of matrices or data frames with functions based on the ggplot2 package.

vis_heatmap(
.data,
.text = TRUE,
.scientific = FALSE,
.signif.digits = 2,
.text.size = 4,
.labs = c("Sample", "Sample"),
.title = "Overlap",
.leg.title = "Overlap values",
.legend = TRUE,
.na.value = NA,
.transpose = FALSE,
...
)

## Arguments

.data Input object: a matrix or a data frame. If matrix: column names and row names (if presented) will be used as names for labs. If data frame: the first column will be used for row names and removed from the data. Other columns will be used for values in the heatmap. If TRUE then plot values in the heatmap cells. If FALSE do not plot values, just plot coloured cells instead. If TRUE then use the scientific notation for numbers (e.g., "2.0e+2"). Number of significant digits to display on plot. Size of text in the cells of heatmap. A character vector of length two with names for x-axis and y-axis, respectively. The The text for the plot's title. The The text for the plots's legend. Provide NULL to remove the legend's title completely. If TRUE then displays a legend, otherwise removes legend from the plot. Replace NA values with this value. By default they remain NA. Logical. If TRUE then switch rows and columns. Other passed arguments.

## Value

A ggplot2 object.

data(immdata)
ov <- repOverlap(immdata$data) vis_heatmap(ov) gu <- geneUsage(immdata$data, "hs.trbj")