Displaying 2 results from an estimated 2 matches for "other_genes".
2016 Apr 05
2
Is that an efficient way to find the overlapped , upstream and downstream ranges for a bunch of ranges
...ownstream_geneoverlapped_gene
gene1NAgene2NA
gene2gene1gene4gene3
gene3gene1gene4gene2
gene4gene3gene5NA
Currently , the strategy I use is like that,
library(GenomicRanges)
find_overlapped_gene <- function(idx, all_genes_gr) {
#cat(idx, "\n")
curr_gene <- all_genes_gr[idx]
other_genes <- all_genes_gr[-idx]
n <- countOverlaps(curr_gene, other_genes)
gene <- subsetByOverlaps(curr_gene, other_genes)
return(list(n, gene))
}?
system.time(lapply(1:100, function(idx) find_overlapped_gene(idx, all_genes_gr)))
However, for 100 genes, it use nearly ~8s by system.time().Th...
2016 Apr 05
0
Is that an efficient way to find the overlapped , upstream and downstream rangess for a bunch of rangess
...e overlapped_gene
gene1 NA gene2 NA
gene2 gene1 gene4 gene3
gene3 gene1 gene4 gene2
gene4 gene3 gene5 NA
Currently , the strategy I use is like that,
library(GenomicRanges)
find_overlapped_gene <- function(idx, all_genes_gr) {
#cat(idx, "\n")
curr_gene <- all_genes_gr[idx]
other_genes <- all_genes_gr[-idx]
n <- countOverlaps(curr_gene, other_genes)
gene <- subsetByOverlaps(curr_gene, other_genes)
return(list(n, gene))
}?
system.time(lapply(1:100, function(idx) find_overlapped_gene(idx,
all_genes_gr)))
However, for 100 genes, it use nearly ~8s by system.time().T...