A More Scalable Alternative to Venn and Euler Diagrams for Visualizing Intersecting Sets
Creates visualizations of intersecting sets using a novel matrix
design, along with visualizations of several common set, element and attribute
related tasks (Conway 2017) <doi:10.1093/bioinformatics/btx364>.
UpSetR generates static UpSet plots. The UpSet technique visualizes set intersections in a matrix layout and introduces aggregates based on groupings and queries. The matrix layout enables the effective representation of associated data, such as the number of elements in the aggregates and intersections, as well as additional summary statistics derived from subset or element attributes.
If you use UpSetR in a paper, please cite:
Jake R Conway, Alexander Lex, Nils Gehlenborg UpSetR: An R Package for the Visualization of Intersecting Sets and their Properties doi: https://doi.org/10.1093/bioinformatics/btx364
The original technique and the interactive visualization tool implementing the approach are described here:
Alexander Lex, Nils Gehlenborg, Hendrik Strobelt, Romain Vuillemot, Hanspeter Pfister,
UpSet: Visualization of Intersecting Sets,
IEEE Transactions on Visualization and Computer Graphics (InfoVis '14), vol. 20, no. 12, pp. 1983–1992, 2014.
Sample data sets for UpSetR are included in the package and can be loaded like this:
movies <- read.csv( system.file("extdata", "movies.csv", package = "UpSetR"), header=T, sep=";" ) mutations <- read.csv( system.file("extdata", "mutations.csv", package = "UpSetR"), header=T, sep = ",")
The movie data set created by the GroupLens Lab and curated by Bilal Alsallakh and the mutations data set was originally created by the TCGA Consortium and represents mutations for the 100 most mutated genes in a glioblastoma multiforme cohort.
There are currently four vignettes that explain how to use the features included in the UpSetR package:
A view of the UpSet plot with additional plots based on elements in the intersections.
upset(movies,attribute.plots=list(gridrows=60,plots=list(list(plot=scatter_plot, x="ReleaseDate", y="AvgRating"), list(plot=scatter_plot, x="ReleaseDate", y="Watches"),list(plot=scatter_plot, x="Watches", y="AvgRating"), list(plot=histogram, x="ReleaseDate")), ncols = 2))
A view of UpSetR mimicking the plot published by Lex & Gehlenborg http://www.nature.com/nmeth/journal/v11/n8/abs/nmeth.3033.html
upset(mutations, sets = c("PTEN", "TP53", "EGFR", "PIK3R1", "RB1"), sets.bar.color = "#56B4E9", order.by = "freq", empty.intersections = "on")
An example using two set queries (war movies and noir movies) along with attribute plots comparing the average rating (top) and average rating vs the number of times the movies have been watched (bottom).
upset(movies, attribute.plots=list(gridrows = 100, ncols = 1, plots = list(list(plot=histogram, x="AvgRating",queries=T), list(plot = scatter_plot, y = "AvgRating", x = "Watches", queries = T))), sets = c("Action", "Adventure", "Children", "War", "Noir"), queries = list(list(query = intersects, params = list("War"), active = T), list(query = intersects, params = list("Noir"))))
Install the latest released version from CRAN
Download the latest development code of UpSetR from GitHub using devtools with
Functions in UpSetR
|elements||Element query for queries parameter|
|fromExpression||Expression to UpSetR converters|
|histogram||Histogram for custom plot|
|fromList||List of named vectors to UpSetR converter|
|intersects||Intersection query for queries parameter|
|scatter_plot||Scatterplot for customplot|
Vignettes of UpSetR
Last month downloads
|License||MIT + file LICENSE|
|Packaged||2019-05-09 16:34:50 UTC; jakeconway|
|Date/Publication||2019-05-22 23:30:03 UTC|
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