I am trying to assembled a pooled metagenomic dataset with 762909004 reads. Will using tools such as BBNorm to downsize the coverage in order to speed up the assembly significantly effect the final assemblies?
To answer your question first: normalizing it down to 100x should have no ill effect, and it may even help reduce the errors if you have very high coverage. Several times I have obtained better assemblies from 60x- or 80x-normalized data than from original datasets. Still, I suggest that you assemble from your original data so you have a baseline. I have assembled about 350 million reads with [**megahit**][1] in about 10 hours - you should be able to do it with your dataset in couple of days. It is always possible the original data is of such quality that it yields the best assembly.


  [1]: https://github.com/voutcn/megahit