Running SHOGUN according to documentation fails with large datasets

[SJohnsonMayo]

Hi all,

I'm trying to run SHOGUN on ~340 shallow shotgun samples, and running it as intended in the documentation doesn't seem to be working. As far as I can tell, BURST is instantly segfaulting when I give it the combined_seqs.fna (667GB) that I get from shi7. Is there any reason why SHOGUN can't be run on the individual samples with the resulting tables joined at the end?

Thanks,

Stephen

[GabeAl]

That will also work! You can combine the OTU tables afterwards. Typically this yields a slight decrease in quality because the capitalist redistribution algorithm won't be able to see all the queries at once to pick the minimal reference set, but with so many samples things should wash out in most cases. Cheerio, Gabe

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On Tue, Nov 19, 2019, 2:24 PM SJohnsonMayo ***@***.***> wrote: Hi all, I'm trying to run SHOGUN on ~340 shallow shotgun samples, and running it as intended in the documentation doesn't seem to be working. As far as I can tell, BURST is instantly segfaulting when I give it the combined_seqs.fna (667GB) that I get from shi7. Is there any reason why SHOGUN can't be run on the individual samples with the resulting tables joined at the end? Thanks, Stephen — You are receiving this because you are subscribed to this thread. Reply to this email directly, view it on GitHub <#27?email_source=notifications&email_token=AB5NOBU62BHJLZGNB7ZT66TQUQ4QXA5CNFSM4JPIFG42YY3PNVWWK3TUL52HS4DFUVEXG43VMWVGG33NNVSW45C7NFSM4H2OEKSQ>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AB5NOBUGUTUMOKZXU2SF2K3QUQ4QXANCNFSM4JPIFG4Q> .

[SJohnsonMayo]

Makes sense, thanks so much for the fast response!