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CSB5 / OPERA-MS

OPERA-MS - Hybrid Metagenomic Assembler
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Optimizing assembly of (very) large metagenomes #53

Open clb21565 opened 3 years ago

clb21565 commented 3 years ago

Dear OPERA-MS creators,

Thanks for the great tool!

I am attempting to assemble a very large and complex metagenome (~5e9 150 bp PE reads or ~ 8e11 basepairs short reads) with about 16 gbs of nanopore reads. I am noticing the read pre-processing with BWA is taking quite a bit of time:

[M::main_mem] read 1544278 sequences (200000192 bp)... [M::mem_process_seqs] Processed 1544278 reads in 429.336 CPU sec, 21.544 real sec

At this rate (~1.5 million reads per ~20 seconds) it would take a very long time to finish this just this task. Would you mind providing guidance on whether or not this is even possible with OPERA-MS? And, if so, how could one go about optimizing the process?

Thank you again.

Cheers,

Connor

nnnagara commented 3 years ago

Dear Connor,

We have indeed assembled datasets of this size though I will let Denis and Chengxuan comment on the runtime,

Regards,

Niranjan

From: Connor Brown notifications@github.com Reply-To: CSB5/OPERA-MS reply@reply.github.com Date: Saturday, 20 February 2021 at 2:02 AM To: CSB5/OPERA-MS OPERA-MS@noreply.github.com Cc: Subscribed subscribed@noreply.github.com Subject: [CSB5/OPERA-MS] Optimizing assembly of (very) large metagenomes (#53)

Dear OPERA-MS creators,

Thanks for the great tool!

I am attempting to assemble a very large and complex metagenome (~5e10 150 bp PE reads or ~ 7e11 basepairs short reads) with about 16 gbs of nanopore reads. I am noticing the read pre-processing with BWA is taking quite a bit of time:

[M::main_mem] read 1544278 sequences (200000192 bp)... [M::mem_process_seqs] Processed 1544278 reads in 429.336 CPU sec, 21.544 real sec

At this rate (~1.5 million reads per ~20 seconds) it would take a very long time to finish this task. Would you mind providing guidance on whether or not this is even possible with OPERA-MS? And, if so, how could one go about accomplishing it?

Thank you again.

Cheers,

Connor

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