Comments (1)
To a first approximation, each neighbor sequence is turned into a suffix array. Since the computation of a suffix array comes with a performance overhead, the analysis of very many sequences in the neighborhood will slow down makeFurDb. One way to speet things up is to concatenate sequences into fewer, longer chunks. In the limit of concatenating all neighbors into one sequence, memory consumption is maximal and might outstrip the avable RAM. Hope this helps.
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Related Issues (17)
- P value input parameter does not affact results HOT 2
- No output for some species HOT 17
- fur error HOT 2
- Single target issue still happening in outdated docker version HOT 2
- Package error in docker image: fur: error while loading shared libraries: libgsl.so.25: cannot open shared object file: No such file or directory HOT 2
- PRIMER_MAX_TM error? HOT 1
- Can not read fasta files HOT 5
- Method of choosing index target representative HOT 1
- Macle.idx is not accessible. HOT 4
- error in fur: efopen HOT 2
- Bug in tutorial HOT 1
- How to select the neighbors genomes? HOT 8
- Error when making fur HOT 4
- Issues on esa HOT 6
- Error when making fur regarding stream HOT 3
- Using docker container HOT 1
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from fur.