Displaying 2 results from an estimated 2 matches for "curr_gen".
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curr_len
2016 Apr 05
2
Is that an efficient way to find the overlapped , upstream and downstream ranges for a bunch of ranges
...ike belows:
gene_nameupstream_genedownstream_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...
2016 Apr 05
0
Is that an efficient way to find the overlapped , upstream and downstream rangess for a bunch of rangess
...ne_name upstream_gene downstream_gene 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 gene...