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UpSet.js is a JavaScript re-implementation of UpSetR which itself is based on UpSet.
The core library is written in React but provides also bundle editions for plain JavaScript use and this R wrapper using HTMLWidget.
In this tutorial the basic widget functionality is explained.
Let’s begin with importing the library
# devtools::install_url("https://github.com/upsetjs/upsetjs_r/releases/latest/download/upsetjs.tar.gz")
library(upsetjs)
Note: The input data will be described in more detail in the next section
example of list input (list of named vectors, each having a list of contained elements)
<- list(one = c("a", "b", "c", "e", "g", "h", "k", "l", "m"), two = c("a",
listInput "b", "d", "e", "j"), three = c("a", "e", "f", "g", "h", "i", "j", "l", "m"))
<- upsetjs() %>%
w fromList(listInput) %>%
interactiveChart()
w
An UpSet plot consists of three areas:
Moving the mouse over a bar or a dot will automatically highlight the corresponding set or set intersection in orange. In addition, the number elements which are shared with the highlighted sets are also highlighted. This gives a quick overview how sets and set intersections are related to each other. More details, in the Interaction section.
In the current version the UpSet.js wrapper supports three input data formats: list, expression, and through a data.frame.
The first format is a list. The key of the list entry is the set name while the value is the vector of elements this set has. See also UpsetR
upsetjs() %>%
fromList(list(one = c("a", "b", "c", "e", "g", "h", "k", "l", "m"), two = c("a",
"b", "d", "e", "j"), three = c("a", "e", "f", "g", "h", "i", "j", "l", "m")))
The second version is a a variant in which not the elements are given but their cardinality. Thus, besides the sets also all the set intersections have to be defined. Moreover, this version has only limited interactivty support.
# example of expression input
<- list(one = 9, two = 5, three = 9, `one&two` = 3, `one&three` = 6,
expressionInput `two&three` = 3, `one&two&three` = 2)
upsetjs() %>%
fromExpression(expressionInput) %>%
interactiveChart()
The last format is a a binary/boolean data frame. The rownames contain the list of elements. Each regular column represents a set with boolean values (e.g., 0 and 1) whether the row represented by the rowname is part of the set or not.
The following data frame defines the same set structure as the dictionary format before.
# boolean table with rows = elements, columns = sets, cell = is row part of
# this set
<- as.data.frame(list(one = c(1, 1, 1, 0, 1, 0, 1, 1, 0, 0, 1, 1, 1), two = c(1,
dataFrame 1, 0, 1, 1, 0, 0, 0, 0, 1, 0, 0, 0), three = c(1, 0, 0, 0, 1, 1, 1, 1, 1, 1,
0, 1, 1)), row.names = c("a", "b", "c", "d", "e", "f", "g", "h", "i", "j", "k",
"l", "m"))
upsetjs() %>%
fromDataFrame(dataFrame)
In case of an expressionInput
the combinations of sets
are directly given.
generateIntersections
,
generateDistinctIntersections
, and
generateUnions
let you customize the generation of the set
combinations
min
… minimum number of sets in a set combinationmax
… maximum number of sets in a set combination, NULL
means no limitempty
… include empty set combinations with no
elements. By default they are not includedorder.by
… sort set combinations either by
cardinality
(number of elements) or by degree
(number of setslimit
… show only the first limit set combinationsupsetjs() %>%
fromList(listInput) %>%
generateDistinctIntersections()
upsetjs() %>%
fromList(listInput) %>%
generateIntersections(min = 2, max = NULL, empty = T, order.by = "cardinality",
limit = NULL)
upsetjs() %>%
fromList(listInput) %>%
generateUnions(min = 0, max = 2, empty = T, order.by = "degree", limit = NULL)
by setting the interactiveFlag
flag, the user can
interactively highlight sets within the chart.
upsetjs() %>%
fromList(listInput) %>%
interactiveChart()
with setSelection
one manually sets the selection that
is currently highlighted. The set is referenced by its name, a vector
with multiple names is detected as an intersection name
upsetjs() %>%
fromList(listInput) %>%
setSelection("one")
upsetjs() %>%
fromList(listInput) %>%
setSelection(c("one", "two"))
In case UpSet.js will be used in a R Shiny context, it reports the current selection based using two custom events:
<outputid>_hover
when the user hovers over an
item<outputid>_click
when the user clicks on an
item<outputid>_contextMenu
when the user right clicks
on an itemboth events are list objects with a name
attribute that
is either NULL
or the name of the set. In addition, there
is an elems
attribute which contains the list of
highlighted elements.
See also Shiny examples at events.R
besides the selection UpSet.js supports defining queries. A query can be a list of elements or a set that should be highlighted. A query consists of a name, a color, and either the list of elements or the set (combination) to highlight.
upsetjs() %>%
fromList(listInput) %>%
addQuery("Q1", color = "red", elems = c("a", "b", "c")) %>%
addQuery("Q2", color = "blue", set = "two")
UpSet.js supports rendering boxplots as aggregations for numerical attributes of elements and mosaic plots for categorical attributes. The are given as part of the data frame. The attributes element has to be a list or a data frame.
<- as.data.frame(list(one = c(1, 1, 1, 0, 1, 0, 1, 1, 0, 0, 1, 1, 1), two = c(1,
dataFrame 1, 0, 1, 1, 0, 0, 0, 0, 1, 0, 0, 0), three = c(1, 0, 0, 0, 1, 1, 1, 1, 1, 1,
0, 1, 1)), row.names = c("a", "b", "c", "d", "e", "f", "g", "h", "i", "j", "k",
"l", "m"))
upsetjs() %>%
fromDataFrame(dataFrame, attributes = list(attr = runif(nrow(dataFrame))))
UpSet.js supports thre themes: light, dark, and vega. The theme can
be set by the chartTheme
function
upsetjs() %>%
fromList(listInput) %>%
chartTheme("dark")
upsetjs() %>%
fromList(listInput) %>%
chartLabels(title = "Chart Title", description = "this is a long chart description")
upsetjs() %>%
fromList(listInput) %>%
chartLabels(combination.name = "Combination Label", set.name = "Set Label")
setting chartLayout(numerical.scale = 'log')
switches to
a log scale, similarly 'linear'
goes back to a linear
scale
upsetjs() %>%
fromList(listInput) %>%
chartLayout(numerical.scale = "log")
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.