I am running:
MosaikJump -ia Genome_cs.dat -out Genome.15 -hs 15
It all looks fine up until it writes the jump database, i.e. it freezes at a certain percentage of completion.
###########################
- retrieving reference sequence... finished.
- hashing reference sequence:
100%[====================================] 3,178,048 hashes/s in 05:46
- serializing final sorting vector... finished.
- writing jump positions database:
25% [======> ] 0.0000 hash positions/s ETA 0 s /
###########################
for another genome (bigger one) i am creating a jumb db it only reaches 10% and then freezes.
###################################
- retrieving reference sequence... finished.
- hashing reference sequence:
100%[====================================] 2,928,603 hashes/s in 15:30
- serializing final sorting vector... finished.
- writing jump positions database:
10% [=> ] 0.0000 hash positions/s ETA 0 s \
##############################
Any suggestions? What ballpark of RAM is suitable for a mammalian/vertebrate genome.
Cheers!
MosaikJump -ia Genome_cs.dat -out Genome.15 -hs 15
It all looks fine up until it writes the jump database, i.e. it freezes at a certain percentage of completion.
###########################
- retrieving reference sequence... finished.
- hashing reference sequence:
100%[====================================] 3,178,048 hashes/s in 05:46
- serializing final sorting vector... finished.
- writing jump positions database:
25% [======> ] 0.0000 hash positions/s ETA 0 s /
###########################
for another genome (bigger one) i am creating a jumb db it only reaches 10% and then freezes.
###################################
- retrieving reference sequence... finished.
- hashing reference sequence:
100%[====================================] 2,928,603 hashes/s in 15:30
- serializing final sorting vector... finished.
- writing jump positions database:
10% [=> ] 0.0000 hash positions/s ETA 0 s \
##############################
Any suggestions? What ballpark of RAM is suitable for a mammalian/vertebrate genome.
Cheers!