Hi, I have 26 lists of genes. I want to extract an overlap of 26 lists for clustering. something like below
> head(inc[,1:4])
31439_f_at 31440_at 31441_at 31442_at
set1 1 1 1 1
set2 0 0 0 0
set3 0 0 0 0
>
I tried ‘GSEABase’, but too complicated. May someone help me please?
Ideally, a matrix with "gene lists" as the columns (ie., gene list 1 in column 1, gene list 2 in column 2, etc.) and rows with the union of all genes. Put a "1" in each cell for a gene that is present in a gene list and "0" elsewhere.
A related question was asked the other day.
gene_lists = list(letters[1:3], letters[3:7], letters[6:8])
There's loads of ways to do this
The solution that @lessismore generated in the comments was effectively:
make_bipartite_adjacency_from_sets <- function(list_of_sets){
universe <- sort(unique(unlist(list_of_sets)))
adjacency_df <- lapply(list_of_sets, function(x) as.numeric(universe %in% x)) %>% as.data.frame()
rownames(adjacency_df) <- universe
adjacency_df
}
make_bipartite_adjacency_from_sets(gene_lists)
G1 G2 G3
a 1 0 0
b 1 0 0
c 1 1 0
d 0 1 0
e 0 1 0
f 0 1 1
g 0 1 1
h 0 0 1
You could also do a tidyverse version (but this disallows row names):
make_bipartite_adjacency_from_sets2 <- function(list_of_sets){
list_of_sets %>%
purrr::map(function(x) tibble::data_frame(gene_id = x, adj = 1)) %>%
dplyr::bind_rows(.id = "set_id") %>%
tidyr::spread(key = set_id, value = adj, fill = 0)
}
make_bipartite_adjacency_from_sets2(gene_lists)
# A tibble: 8 x 4
gene_id G1 G2 G3
* <chr> <dbl> <dbl> <dbl>
1 a 1 0 0
2 b 1 0 0
3 c 1 1 0
4 d 0 1 0
5 e 0 1 0
6 f 0 1 1
7 g 0 1 1
8 h 0 0 1
Thank you, the problem is I can't figure out how make a gene list. For instance, how make gene list or gene set1 by a column of genes?
I made GS1 like this screenshot
but says
> make_bipartite_adjacency_from_sets(gene_lists)
Error in attributes(.Data) <- c(attributes(.Data), attrib) :
'names' attribute [1704] must be the same length as the vector [2]
Called from: structure(res, levels = lv, names = nm, class = "factor")
Browse[1]>
Thanks a lot, without your help definitely I could not figure out for at least 2 weeks...
I did so;
library(igraph)
GS1=c(t(GS1))
GS2=c(t(GS2))
gene_lists = list(c(GS1), c(GS2))
make_bipartite_adjacency_from_sets <- function(list_of_sets){
universe <- sort(unique(unlist(list_of_sets)))
adjacency_df <- lapply(list_of_sets, function(x) as.numeric(universe %in% x)) %>% as.data.frame()
rownames(adjacency_df) <- universe
adjacency_df
}
make_bipartite_adjacency_from_sets(gene_lists)
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