library(circlize)
library(ComplexHeatmap)
library(GetoptLong)
set.seed(123)
lt = list(a = sample(letters, 10),
b = sample(letters, 15),
c = sample(letters, 20))
m = make_comb_mat(lt)
t(m)
set_name(m)
comb_name(m)
set_size(m)
comb_size(m)
lapply(comb_name(m), function(x) extract_comb(m, x))
draw(UpSet(m))
draw(UpSet(m, comb_col = c(rep(2, 3), rep(3, 3), 1)))
draw(UpSet(t(m)))
set_name(t(m))
comb_name(t(m))
set_size(t(m))
comb_size(t(m))
lapply(comb_name(t(m)), function(x) extract_comb(t(m), x))
m = make_comb_mat(lt, mode = "intersect")
lapply(comb_name(m), function(x) extract_comb(m, x))
draw(UpSet(m))
m = make_comb_mat(lt, mode = "union")
lapply(comb_name(m), function(x) extract_comb(m, x))
draw(UpSet(m))
f = system.file("extdata", "movies.csv", package = "UpSetR")
if(file.exists(f)) {
movies <- read.csv(system.file("extdata", "movies.csv", package = "UpSetR"), header = T, sep = ";")
m = make_comb_mat(movies, top_n_sets = 6)
t(m)
set_name(m)
comb_name(m)
set_size(m)
comb_size(m)
lapply(comb_name(m), function(x) extract_comb(m, x))
set_name(t(m))
comb_name(t(m))
set_size(t(m))
comb_size(t(m))
lapply(comb_name(t(m)), function(x) extract_comb(t(m), x))
draw(UpSet(m))
draw(UpSet(t(m)))
m = make_comb_mat(movies, top_n_sets = 6, mode = "intersect")
m = make_comb_mat(movies, top_n_sets = 6, mode = "union")
}
library(circlize)
library(GenomicRanges)
lt = lapply(1:4, function(i) generateRandomBed())
lt = lapply(lt, function(df) GRanges(seqnames = df[, 1], ranges = IRanges(df[, 2], df[, 3])))
names(lt) = letters[1:4]
m = make_comb_mat(lt)
# if(0) {
# set.seed(123)
# lt = list(a = sample(letters, 10),
# b = sample(letters, 15),
# c = sample(letters, 20))
# v = gplots::venn(lt, show.plot = FALSE)
# rownames(v) = apply(v[, -1], 1, paste, collapse = "")
# m = make_comb_mat(lt)
# cs = structure(comb_size(m), names = comb_name(m))
# }
if(file.exists(f)) {
movies <- read.csv(f, header = T, sep = ";")
genre = c("Action", "Romance", "Horror", "Children", "SciFi", "Documentary")
rate = cut(movies$AvgRating, c(0, 1, 2, 3, 4, 5))
m_list = tapply(seq_len(nrow(movies)), rate, function(ind) {
make_comb_mat(movies[ind, genre, drop = FALSE])
})
m_list2 = normalize_comb_mat(m_list)
lapply(m_list2, set_name)
lapply(m_list2, set_size)
lapply(m_list2, comb_name)
lapply(m_list2, comb_size)
lapply(1:length(m_list), function(i) {
n1 = comb_name(m_list[[i]])
x1 = comb_size(m_list[[i]])
n2 = comb_name(m_list2[[i]])
x2 = comb_size(m_list2[[i]])
l = n2 %in% n1
x2[!l]
})
}
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