Color_Palette.RmdIn itol, most templates need users to specify color information
manually, causing inconvenience when preparing large amounts of data for
visualization. Therefore, itol.toolkit has been optimized to address
this issue by allowing users to input only metadata, and the program
will automatically generates corresponding color information through the
built-in color palette. To best meet the needs of different users, there
are several palettes in itol.toolkit for users to select, and, of
course, itol.toolkit retaining the choice of setting colors manually. In
addition, the limited number of colors provided in some existing itol
helper packages makes it difficult to meet the user’s usage needs when
the user has a large amount of data. itol.toolkit provides up to 75
colors, which basically meets the user’s usage needs. Users can modify
the color palette by “color” parameter of the create_unit()
function.
This section describes several ways to modify the color scheme when
creating a unit with itol.toolkit. To show each color
scheme more visually, we use dataset3
and the DATASET_COLORSTRIP template for demonstration.
Users can download the data locally from the provided link above. The
files are read using a relative path in this document, so please adjust
the path based on your actual situation.
Before we start, please load the packages and data.
“table2itol” is the default color palette used by the widely used table2itol.R tool, and itol.toolkit inherent. When the user does not set the color parameter when creating a unit, the program will use this color palette by default. The color palette supports up to 40 different colors, which is sufficient for most users when annotating taxonomic information. However, it may not be adequate for users with large trees or when annotating lower taxonomic ranks (e.g., genus, species).
unit_1 <- create_unit(data = df_data %>% select(ID, Class),
key = "color_table2itol_1",
type = "DATASET_COLORSTRIP",
tree = tree)When the default color palette is insufficient, the user can set the color parameter to “wesanderson” color palette (Refer to wesanderson for more detail information). The color palette supports up to 75 different colors, which can meet most of users’ needs.
unit_2 <- create_unit(data = df_data %>% select(ID, Genus),
key = "color_wesanderson_1",
type = "DATASET_COLORSTRIP",
color = "wesanderson",
tree = tree)Note that different random number seeds will produce different color
schemes when using the wesanderson color palette, so it is recommended
to set a random number seed using the set.seed() function
before using it.
set.seed(123)
unit_3 <- create_unit(data = df_data %>% select(ID, Genus),
key = "color_wesanderson_2",
type = "DATASET_COLORSTRIP",
color = "wesanderson",
tree = tree)RColorBrewer package provides three categories of 44 color palettes
(refer to the ColorBrewer2 for
detail information), users can view these palettes through
display.brewer.all() function.
library(RColorBrewer)
display.brewer.all()itol.toolkit supports using the RColorBrewer color palette. Note that when creating a unit using the RColorBrewer color palette, users need to set the “color” parameter to the name of the palette in RColorBrewer instead of setting it directly to “RColorBrewer”.
unit_4 <- create_unit(data = df_data %>% select(ID, Phylum),
key = "color_RColorBrewer_1",
type = "DATASET_COLORSTRIP",
color = "Set1",
tree = tree)
unit_5 <- create_unit(data = df_data %>% select(ID, Phylum),
key = "color_RColorBrewer_2",
type = "DATASET_COLORSTRIP",
color = "Set3",
tree = tree)ggsci package offers a collection of high-quality color palettes inspired by colors used in scientific journals, data visualization libraries, science fiction movies, and TV shows (refer to the ggsci for detail information). itol.toolkit has built-in ggsci color palettes, and users can use these color palettes by setting the “color” parameter. Note that when creating a unit using the ggsci color palette, users need to set the “color” parameter to the name of the palette in ggsci instead of setting it directly to “ggsci”.
unit_6 <- create_unit(data = df_data %>% select(ID, Phylum),
key = "color_ggsci_1",
type = "DATASET_COLORSTRIP",
color = "npg",
tree = tree)If different types exist for the color palettes, use an underscore
_ to separate the palettes name from the type.
unit_7 <- create_unit(data = df_data %>% select(ID, Phylum),
key = "color_ggsci_2",
type = "DATASET_COLORSTRIP",
color = "d3_category10",
tree = tree)
unit_8 <- create_unit(data = df_data %>% select(ID, Phylum),
key = "color_ggsci_3",
type = "DATASET_COLORSTRIP",
color = "d3_category8",
tree = tree)Users can set the colors manually by adding columns containing color information to the metadata. The program supports hexadecimal, RGB, and RGBA color formats and automatically recognizes strings starting with “#” or “rgb” as color information.
phylum_color <- tribble(
~Phylum, Phylum_color,
"Proteobacteria", "#5a7860",
"Actinobacteria", "#92af83",
"Firmicutes", "#f1e0a8",
"Nitrospirae", "#dd7050",
"Bacteroidetes", "#cca663"
)
df_data <- df_data %>%
left_join(phylum_color)
unit_9 <- create_unit(data = df_data %>%
select(ID, Phylum, Phylum_color),
key = "color_manual_1",
type = "DATASET_COLORSTRIP",
tree = tree)
phylum_color <- tribble(
~Phylum, Phylum_color,
"Proteobacteria", "rgb(16, 70, 128)",
"Actinobacteria", "rgb(109, 173, 209)",
"Firmicutes", "rgb(233, 241, 244)",
"Nitrospirae", "rgb(220, 109, 87)",
"Bacteroidetes", "rgb(183, 34, 48)"
)
df_data <- df_data %>%
left_join(phylum_color)
unit_10 <- create_unit(data = df_data %>%
select(ID, Phylum, Phylum_color),
key = "color_manual_2",
type = "DATASET_COLORSTRIP",
tree = tree)
phylum_color <- tribble(
~Phylum, Phylum_color,
"Proteobacteria", "rgba(16, 70, 128, 0.8)",
"Actinobacteria", "rgba(109, 173, 209, 0.8)",
"Firmicutes", "rgba(233, 241, 244, 0.8)",
"Nitrospirae", "rgba(220, 109, 87, 0.8)",
"Bacteroidetes", "rgba(183, 34, 48, 0.8)"
)
df_data <- df_data %>%
left_join(phylum_color)
unit_11 <- create_unit(data = df_data %>%
select(ID, Phylum, Phylum_color),
key = "color_manual_3",
type = "DATASET_COLORSTRIP",
tree = tree)IOCAS, weiyLiu@outlook.com↩︎
CACMS, njbxhzy@hotmail.com↩︎
IOCAS, tongzhou2017@gmail.com↩︎