View source: R/onco.print.props.R
| onco.print.props | R Documentation |
Calculates and assigns the proportion of each oncoprint rectangle to be color-filled based on the average size of lesion types. Lesion types are ordered by their average genomic size, and proportions are either computed automatically or manually specified by the user.
onco.print.props(lsn.data, clr = NULL, hgt = NULL)
lsn.data |
A data frame with five columns:
Lesion type names in |
clr |
Optional. A named vector of colors for each lesion type.
User-specified colors are preserved and matched to lesion types by name.
If not provided, default colors are assigned using
|
hgt |
Optional. A named numeric vector specifying the proportion (height) of the oncoprint rectangle to be filled for each lesion type. If not provided, proportions are determined automatically based on average lesion sizes. |
In cases where a patient has multiple types of lesions (e.g., gain and mutation) in the same gene, this function ensures that all lesion types are visually represented within a single oncoprint rectangle.
If hgt is not specified, lesion types are ranked by their average
genomic size (calculated as loc.end - loc.start + 1), and the
oncoprint proportions are derived accordingly. Smaller lesions (such as
point mutations) occupy a smaller portion of the rectangle, while larger
lesions (such as copy-number alterations) occupy a larger portion.
Alternatively, the user can manually define the fill proportions using
the hgt parameter.
Colors can be manually specified using a named vector supplied to
clr. When custom colors are provided, they are matched to lesion
types by name and retained in the resulting oncoprint settings.
A list with the following components:
alter_func: A list of alteration-drawing functions for
rendering the different lesion types in the oncoprint.
col: A named vector of colors assigned to each lesion type.
heatmap_legend_param: Legend parameters for the oncoprint.
Lakshmi Patibandla LakshmiAnuhya.Patibandla@stjude.org, Abdelrahman Elsayed abdelrahman.elsayed@stjude.org, Stanley Pounds stanley.pounds@stjude.org
Cao, X., Elsayed, A. H., & Pounds, S. B. (2023). Statistical Methods Inspired by Challenges in Pediatric Cancer Multi-omics.
data(lesion_data)
# Automatically assign oncoprint proportions based on average lesion size:
onco.props <- onco.print.props(lesion_data)
# Manually specify the oncoprint fill proportions for each lesion type:
onco.props <- onco.print.props(
lesion_data,
hgt = c(
"gain" = 4,
"loss" = 3,
"mutation" = 2,
"fusion" = 1
)
)
# Specify custom colors for lesion types:
custom.colors <- c(
"gain" = "red",
"loss" = "blue",
"mutation" = "olivedrab",
"fusion" = "black"
)
onco.props <- onco.print.props(
lesion_data,
clr = custom.colors
)
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