How do I efficiently perform a metagenome screen of “all” species? I’ve got an RNA-seq dataset with a large proportion of environmental RNA “contamination”. BLASTing random reads reveals that much of the data comes from bacterial, plant and viral RNA. My target organism only accounts for ~5% of the RNA-seq read data.

I would like to get a more or less (more, if possible) comprehensive overview of what species are found in my sample — bacteria, plants, animals (?), but also viruses. How can I perform this?

I have been unable to find a “standard” way of performing a metagenome screen. BLAST online services all seem to be severely rate limited (certainly unable to handle uploading ~80 M reads). Installing BLAST (or a similar tool) locally is of course not an issue, but I can’t find a comprehensive database that spans all phyla — the best I’ve been able to find are databases, such as NCBI-NR, that are restricted to single phyla or classes, or to bacteria.

Ideally I’d like a workflow that I feed with my RNA-seq data, and get out a list of species with % of reads mapped.
As you point out, BLAST is not going to work well for reads from a typical RNASeq experiment.

From an RNASeq dataset, you might be able to get away with just a ribosomal screen using Silva, because the ribosome is the most abundantly transcribed gene. This will usually be the case even if polyA selection or ribosomal depletion was carried out on a sample.

However, bear in mind that there will be a lot of false results due to database incompleteness. I used Kraken when I did something like this a few years ago, and ended up with one sequence annotated as a fruit bat (where my subject was a water-living planarian flatworm). Centrifuge would be a better option now; the authors even claim that they can store the entirety of nr in a 70 GB index with Centrifuge (which would be better / more comprehensive than just a ribosomal screen).