R/methods.R
heatmap-methods.Rd
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 = "row", palette_value = c("#440154FF", "#21908CFF", "#fefada"), palette_grouping = list(), annotation = NULL, type = rep("tile", length(quo_names(annotation))), palette_discrete = list(), palette_continuous = list(), .abundance = NULL, .horizontal = NULL, .vertical = NULL, log_transform = NULL, palette_abundance = NULL, ... ) heatmap_( .data, .row, .column, .value, transform = NULL, .scale = "row", palette_value = c("#440154FF", "#21908CFF", "#fefada"), palette_grouping = list(), annotation = NULL, type = rep("tile", length(quo_names(annotation))), palette_discrete = list(), palette_continuous = list(), .abundance = NULL, .horizontal = NULL, .vertical = NULL, log_transform = NULL, palette_abundance = NULL, ... ) # S4 method for tbl heatmap( .data, .row, .column, .value, transform = NULL, .scale = "row", palette_value = c("#440154FF", "#21908CFF", "#fefada"), palette_grouping = list(), annotation = NULL, type = rep("tile", length(quo_names(annotation))), palette_discrete = list(), palette_continuous = list(), .abundance = NULL, .horizontal = NULL, .vertical = NULL, log_transform = NULL, palette_abundance = NULL, ... ) # S4 method for tbl_df heatmap( .data, .row, .column, .value, transform = NULL, .scale = "row", palette_value = c("#440154FF", "#21908CFF", "#fefada"), palette_grouping = list(), annotation = NULL, type = rep("tile", length(quo_names(annotation))), palette_discrete = list(), palette_continuous = list(), .abundance = NULL, .horizontal = NULL, .vertical = NULL, log_transform = NULL, palette_abundance = NULL, ... ) # S4 method for tidybulk heatmap( .data, .row, .column, .value, transform = NULL, .scale = "row", palette_value = c("#440154FF", "#21908CFF", "#fefada"), palette_grouping = list(), annotation = NULL, type = rep("tile", length(quo_names(annotation))), palette_discrete = list(), palette_continuous = list(), .abundance = NULL, .horizontal = NULL, .vertical = NULL, log_transform = NULL, palette_abundance = NULL, ... )
.data | A `tbl_df` formatted as | <ELEMENT> | <FEATURE> | <VALUE> | <...> | |
---|---|
.row | The name of the column vertically presented in the heatmap |
.column | The name of the column horizontally presented in the heatmap |
.value | The name of the column for the value of the element/feature pair |
transform | A function, used to transform .value row-wise (e.g., transform = log1p) |
.scale | A character string. Possible values are c(\"none\", \"row\", \"column\", \"both\") |
palette_value | A character vector This is the palette that will be used as gradient for .value. For higher flexibility you can use circlize::colorRamp2\(c\(-2, -1, 0, 1, 2\), viridis::magma\(5\)\) |
palette_grouping | A list of character vectors. This is the list of palettes that will be used for grouping |
annotation | DEPRECATED. please use the annotation functions add_* function \(\* one of tile, point, bar, line \). |
type | DEPRECATED. please use the annotation functions add_* function \(\* one of tile, point, bar, line \). |
palette_discrete | DEPRECATED. please use the annotation functions add_* function \(\* one of tile, point, bar, line \). |
palette_continuous | DEPRECATED. please use the annotation functions add_* function \(\* one of tile, point, bar, line \). |
.abundance | DEPRECATED. Please use .value instead |
.horizontal | DEPRECATED. Please use .column instead |
.vertical | DEPRECATED. Please use .row instead |
log_transform | DEPRECATED. Please use transform instead |
palette_abundance | DEPRECATED. Please use palette_value instead |
... | Further arguments to be passed to ComplexHeatmap::Heatmap |
A `InputHeatmap` objects that gets evaluated to a `ComplexHeatmap` object
A `InputHeatmap` object
A `InputHeatmap` object
A `InputHeatmap` object
A `InputHeatmap` object
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.
library(dplyr) tidyHeatmap::N52 %>% group_by( `Cell type`) %>% tidyHeatmap::heatmap( .row = symbol_ct, .column = UBR, .value = `read count normalised log`, )