trans_venn {microeco} | R Documentation |
Create trans_venn
object for the Venn diagram, petal plot and UpSet plot.
Description
This class is a wrapper for a series of intersection analysis related methods, including 2- to 5-way venn diagram, more than 5-way petal or UpSet plot and intersection transformations based on David et al. (2012) <doi:10.1128/AEM.01459-12>.
Methods
Public methods
Method new()
Usage
trans_venn$new(dataset, ratio = NULL, name_joint = "&")
Arguments
dataset
the object of
microtable
class or a matrix-like table (data.frame or matrix object). If dataset is a matrix-like table, features must be rows.ratio
default NULL; NULL, "numratio" or "seqratio"; "numratio": calculate the percentage of feature number; "seqratio": calculate the percentage of feature abundance; NULL: no additional percentage.
name_joint
default "&"; the joint mark for generating multi-sample names.
Returns
data_details
and data_summary
stored in the object.
Examples
\donttest{ data(dataset) t1 <- dataset$merge_samples("Group") t1 <- trans_venn$new(dataset = t1, ratio = "numratio") }
Method plot_venn()
Plot venn diagram.
Usage
trans_venn$plot_venn( color_circle = RColorBrewer::brewer.pal(8, "Dark2"), fill_color = TRUE, text_size = 4.5, text_name_size = 6, text_name_position = NULL, alpha = 0.3, linesize = 1.1, petal_plot = FALSE, petal_color = "#BEAED4", petal_color_center = "#BEBADA", petal_a = 4, petal_r = 1, petal_use_lim = c(-12, 12), petal_center_size = 40, petal_move_xy = 4, petal_move_k = 2.3, petal_move_k_count = 1.3, petal_text_move = 40, other_text_show = NULL, other_text_position = c(2, 2), other_text_size = 5 )
Arguments
color_circle
default
RColorBrewer::brewer.pal(8, "Dark2")
; color pallete.fill_color
default TRUE; whether fill the area color.
text_size
default 4.5; text size in plot.
text_name_size
default 6; name size in plot.
text_name_position
default NULL; name position in plot.
alpha
default .3; alpha for transparency.
linesize
default 1.1; cycle line size.
petal_plot
default FALSE; whether use petal plot.
petal_color
default "#BEAED4"; color of the petals; If petal_color only has one color value, all the petals will be assigned with this color value. If petal_color has multiple colors, and the number of color values is smaller than the petal number, the function can append more colors automatically with the color interpolation.
petal_color_center
default "#BEBADA"; color of the center in the petal plot.
petal_a
default 4; the length of the ellipse.
petal_r
default 1; scaling up the size of the ellipse.
petal_use_lim
default c(-12, 12); the width of the plot.
petal_center_size
default 40; petal center circle size.
petal_move_xy
default 4; the distance of text to circle.
petal_move_k
default 2.3; the distance of title to circle.
petal_move_k_count
default 1.3; the distance of data text to circle.
petal_text_move
default 40; the distance between two data text.
other_text_show
default NULL; other characters used to show in the plot.
other_text_position
default c(1, 1); the text position for text in
other_text_show
.other_text_size
default 5; the text size for text in
other_text_show
.
Returns
ggplot.
Examples
\donttest{ t1$plot_venn() }
Method plot_bar()
Plot the intersections using histogram, i.e. UpSet plot. Especially useful when samples > 5.
Usage
trans_venn$plot_bar( left_plot = TRUE, sort_samples = FALSE, up_y_title = "Intersection size", up_y_title_size = 15, up_y_text_size = 8, up_bar_fill = "grey70", up_bar_width = 0.9, bottom_y_text_size = 12, bottom_height = 1, bottom_point_size = 3, bottom_point_color = "black", bottom_background_fill = "grey95", bottom_background_alpha = 1, bottom_line_width = 0.5, bottom_line_colour = "black", left_width = 0.3, left_bar_fill = "grey70", left_bar_alpha = 1, left_bar_width = 0.9, left_x_text_size = 10, left_background_fill = "white", left_background_alpha = 1 )
Arguments
left_plot
default TRUE; whether add the left bar plot to show the feature number of each sample.
sort_samples
default FALSE;
TRUE
is used to sort samples according to the number of features in each sample.FALSE
means the sample order is same with that in sample_table of the raw dataset.up_y_title
default "Intersection set"; y axis title of upper plot.
up_y_title_size
default 15; y axis title size of upper plot.
up_y_text_size
default 4; y axis text size of upper plot.
up_bar_fill
default "grey70"; bar fill color of upper plot.
up_bar_width
default 0.9; bar width of upper plot.
bottom_y_text_size
default 12; y axis text size, i.e. sample name size, of bottom sample plot.
bottom_height
default 1; bottom plot height relative to the upper bar plot. 1 represents the height of bottom plot is same with the upper bar plot.
bottom_point_size
default 3; point size of bottom plot.
bottom_point_color
default "black"; point color of bottom plot.
bottom_background_fill
default "grey95"; fill color for the striped background in the bottom sample plot. If the parameter length is 1, use "white" to distinguish the color stripes. If the parameter length is greater than 1, use all provided colors.
bottom_background_alpha
default 1; the color transparency for the parameter
bottom_background_fill
.bottom_line_width
default 0.5; the line width in the bottom plot.
bottom_line_colour
default "black"; the line color in the bottom plot.
left_width
default 0.3; left bar plot width relative to the right bottom plot.
left_bar_fill
default "grey70"; fill color for the left bar plot presenting feature number.
left_bar_alpha
default 1; the color transparency for the parameter
left_bar_fill
.left_bar_width
default 0.9; bar width of left plot.
left_x_text_size
default 10; x axis text size of the left bar plot.
left_background_fill
default "white"; fill color for the striped background in the left plot. If the parameter length is 1, use "white" to distinguish the color stripes. If the parameter length is greater than 1, use all provided colors.
left_background_alpha
default 1; the color transparency for the parameter
left_background_fill
.
Returns
a ggplot2 object.
Examples
\donttest{ t2 <- t1$plot_bar() }
Method trans_comm()
Transform intersection result to community-like microtable object for further composition analysis.
Usage
trans_venn$trans_comm(use_frequency = TRUE)
Arguments
use_frequency
default TRUE; whether only use OTUs occurrence frequency, i.e. presence/absence data; if FALSE, use abundance data.
Returns
a new microtable
class.
Examples
\donttest{ t2 <- t1$trans_comm(use_frequency = TRUE) }
Method print()
Print the trans_venn object.
Usage
trans_venn$print()
Method clone()
The objects of this class are cloneable with this method.
Usage
trans_venn$clone(deep = FALSE)
Arguments
deep
Whether to make a deep clone.
Examples
## ------------------------------------------------
## Method `trans_venn$new`
## ------------------------------------------------
data(dataset)
t1 <- dataset$merge_samples("Group")
t1 <- trans_venn$new(dataset = t1, ratio = "numratio")
## ------------------------------------------------
## Method `trans_venn$plot_venn`
## ------------------------------------------------
t1$plot_venn()
## ------------------------------------------------
## Method `trans_venn$plot_bar`
## ------------------------------------------------
t2 <- t1$plot_bar()
## ------------------------------------------------
## Method `trans_venn$trans_comm`
## ------------------------------------------------
t2 <- t1$trans_comm(use_frequency = TRUE)