heatmap | R Documentation |
heatmap() takes a tbl object and easily produces a ComplexHeatmap plot, with integration with tibble and dplyr frameworks.
heatmap(
.data,
.row,
.column,
.value,
transform = NULL,
scale = "none",
palette_value = c("#440154FF", "#21908CFF", "#fefada"),
palette_grouping = list(),
.scale = NULL,
...
)
heatmap_(
.data,
.row,
.column,
.value,
transform = NULL,
scale = "none",
palette_value = c("#440154FF", "#21908CFF", "#fefada"),
palette_grouping = list(),
.scale = NULL,
...
)
## S4 method for signature 'tbl'
heatmap(
.data,
.row,
.column,
.value,
transform = NULL,
scale = "none",
palette_value = c("#440154FF", "#21908CFF", "#fefada"),
palette_grouping = list(),
.scale = NULL,
...
)
## S4 method for signature 'tbl_df'
heatmap(
.data,
.row,
.column,
.value,
transform = NULL,
scale = "none",
palette_value = c("#440154FF", "#21908CFF", "#fefada"),
palette_grouping = list(),
.scale = NULL,
...
)
.data |
A 'tbl_df' formatted as | <ELEMENT> | <FEATURE> | <VALUE> | <...> | |
.row |
The name of the column to use as rows |
.column |
The name of the column to use as columns |
.value |
The name of the column to use as values |
transform |
A function to transform the data (optional) |
scale |
One of "none", "row", "column", or "both" for scaling |
palette_value |
A character vector of colors or a function for value colors |
palette_grouping |
A list of color palettes for grouping annotations |
.scale |
DEPRECATED: Use scale instead |
... |
Additional arguments passed to ComplexHeatmap |
maturing
This function takes a tbl as an input and creates a 'ComplexHeatmap' plot. The information is stored in a 'InputHeatmap' object that is updated along the pipe statement, for example adding annotation layers.
An 'InputHeatmap' object that gets evaluated to a 'ComplexHeatmap'
A 'InputHeatmap' object
A 'InputHeatmap' object
A 'InputHeatmap' object
[Mangiola and Papenfuss., 2020](https://joss.theoj.org/papers/10.21105/joss.02472)
Mangiola, S. and Papenfuss, A.T., 2020. "tidyHeatmap: an R package for modular heatmap production based on tidy principles." Journal of Open Source Software. doi:10.21105/joss.02472.
tidyHeatmap::N52 |>
dplyr::group_by( `Cell type`) |>
tidyHeatmap::heatmap(
.row = symbol_ct,
.column = UBR,
.value = `read count normalised log`,
)
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