I also assembled parts of the reads/used digital normalization so that I could assemble and found many bacterial contigs in the assembly. You are right that there is no guarantee that my bacteria are in the reference set but at least I will be able to reduce the size of the original dataset. I could be wrong but if I require that both paired ends (101bp) align concordantly to the bacterial db the false positive rate would be low.
The reason for the original filtering is I cannot assemble due to the size of the dataset. I could assemble with digital normalization and then go from there with your idea.
Thanks for your help!
If you are not looking for novel viral sequences then perhaps doing the binning in reverse may be better. Get the RefSeq viral sequences from here and then use BBSplit to bin the reads into virii and rest.
Thanks for your clarification: I am looking for novel viral sequences, so I want to filter using close alignment to known bacterial species. Asssembling part then aligning original reads to identified contaminants could work but their are too many different bacterial contaminant to make this practical
If novel things is the requirement then slogging though multiple rounds of alignments/assembly may be order of the day. As @Brian noted below this process is going to be fraught with hurdles and you are likely to hit many false positives along the way. I don't see an easy solution.
Have you checked Kraken or Kaiju to do the binning? You can even use MG-RAST to do the taxonomic classification and then download only the viral reads.
Kaiju will work with only 50GB RAM. You can also use the web server and upload your reads there for taxonomic classification.