UpSetPlot

About

UpSet plots (https://en.wikipedia.org/wiki/UpSet_plot) are a data visualization method for showing set data with more than three intersecting sets. UpSet plots tend to perform better than Venn diagrams for larger numbers of sets and when it is desirable to also show contextual information about the set intersections.

Installation

Install UpSetPlot.jl by running the following commands in the Julia REPL:

julia> using Pkg
julia> Pkg.add("UpSetPlot")

Alternatively, in the Julia REPL type ], then

(@v1.12) pkg> add UpSetPlot

Usage

The main function is upset_plot, which returns the UpSet plot computed from:

• Sets stored in a Vector{Set}.

upset_plot(
    sets::Vector{T},
    set_names::Vector{String};
    fig_size::Tuple{Int64, Int64} = (1000, 1000),
    colors::Vector{Symbol} = my25colors, # a vector of named colors
    orientation::Symbol = :vertical,
    cardinality_sort::Bool = false,
    cumul::Bool = false,
    intersection_lists::Bool = false
) where T<:Set

• Sets stored in a dataframe's columns.

upset_plot(
    df::DataFrame;
    set_names::Vector{String} = setdiff(names(df), ["id"]),
    fig_size::Tuple{Int64, Int64} = (1000, 1000),
    colors::Vector{Symbol} = my25colors,
    orientation::Symbol = :vertical,
    cardinality_sort::Bool = false,
    cumul::Bool = false,
    intersection_lists::Bool = false
)

In the latter case, the sets can be encoded in two different ways:

• df's columns whose name is in set_names include the set elements; missings are not considered set elements and deleted.
• One column, named :id, includes all possible elements, and the columns whose name is in set_names include booleans to encode set membership.

Columns not in set_names are not further considered. Columns whose name is in set_names are excluded if they are empty or contain only missings.

orientation sets the orientation of the Intersection size barplot.

If cardinality_sort is true, the Intersection Size barplot is sorted by set cardinality.

If cumul is true, the UpSet plot includes an additional plot displaying the cumulative intersection size for each intersection degree.

If intersection_lists is true, upset_plot additionally returns a Dict whose keys are concatenated set names and values are vectors of elements specific to the intersection of sets found in the concatenated set names. The Dict storing the intersection-specific elements may be converted to a dataframe using the to_dataframe function..

Example

julia> using UpSetPlot
julia> using DataFrames
julia> set_names = ["Set1", "Set2", "Set3", "Set4", "Set5", "Set6"]
julia> df1 = DataFrame(
    Set1 = ["ID01", "ID02", "ID03", "ID07", "ID08", "ID09", "ID10", "ID04", "ID05", "ID06"],
    Set2 = ["ID01", "ID02", "ID03", "ID04", "ID05", "ID11", "ID12", "ID13", "ID14", "ID15"],
    Set3 = ["ID01", "ID02", "ID03", "ID07", "ID13", missing, missing, missing, missing, missing],
    Set4 = ["ID16", "ID17", "ID18", "ID19", "ID14", "ID02", "ID03", missing, missing, missing],
    Set5 = fill(missing, 10),
    Set6 = ["ID01", "ID02", "ID03", "ID04", "ID05", "ID11", "ID12", "ID13", "ID16", missing],
    Col_x = ["x1", "x2", "x3", "x4", "x5", "x6", "x7", "x8", "x9", "x10"]
)
julia> df2 = DataFrame(
    id = ["ID01", "ID02", "ID03", "ID04", "ID05", "ID06", "ID07", "ID08", "ID09", "ID10", "ID11", "ID12", "ID13", "ID14", "ID15", "ID16", "ID17", "ID18", "ID19"],
    Set1 = [true, true, true, true, true, true, true, true, true, true, false, false, false, false, false, false, false, false, false],
    Set2 = [true, true, true, true, true, false, false, false, false, false, true, true, true, true, true, false, false, false, false],
    Set3 = [true, true, true, false, false, false, true, false, false, false, false, false, true, false, false, false, false, false, false],
    Set4 = [false, true, true, false, false, false, false, false, false, false, false, false, false, true, false, true, true, true, true],
    Set5 = fill(false, 19),
    Set6 = [true, true, true, true, true, false, false, false, false, false, true, true, true, false, false, true, false, false, false]
)
julia> fig1, lists1 = upset_plot(df1; set_names=set_names, intersection_lists=true);
julia> fig2, lists2 = upset_plot(df2; orientation=:h, cumul=true, intersection_lists=true);
julia> lists_1 == lists_2
true
julia> lists1["Set1"] == ["ID06", "ID08", "ID09", "ID10"]
true
julia> lists2["Set1_Set2_Set6"] == ["ID04", "ID05"]
true
julia> to_dataframe(lists1)

julia> display(fig1)

julia> display(fig2)

julia> fig = upset_plot(df1; set_names=set_names, fig_size=(750, 750), orientation=:v, cardinality_sort=true, cumul=true, intersection_lists=false)