Frequently Asked Questions

Can I use another version of GTDB for annotation?

Yes. There are two approaches:

1. Download an mmseqs-formatted GTDB (the command mmseqs databases GTDB GTDB tmp will download the latest version). Then, point SemiBin to this database using the --reference-db-data-dir option.
2. Precompute the contig annotations with mmseqs using any version of GTDB and pass the contig annotation table to SemiBin using the taxonomy-annotation-table option. Do note that the tool expects an mmseqs formatted file and is likely to produce nonsensical results if a different format is provided.

The second approach is more complex but can make sense as part of a larger pipeline where taxonomic annotation of contigs is performed for multiple reasons (not only for the benefit of SemiBin).

Does SemiBin work with long-read data?

Technically, yes, you can apply it to long-read data and it will produce bins. However, SemiBin is not optimized for this setting and all the benchmarking in the manuscript is performed on short-read assemblies. You may consider using SemiBin as part of a multi-algorithm approach followed by dereplication, but on its own it will be likely outperformed by methods specifically addressing long-read data (e.g., GraphMB).

How to adapt the approach of SemiBin to long-read data is part of ongoing research. We are very keen to test these approaches. Please, feel free get it touch (shaojun@big-data-biology.org or luispedro@big-data-biology.org) if you have any long-read data that you'd be willing to share and we will attempt to provide you with the resulting bins.

Does SemiBin work for eukaryotic genomes?

The answer given above for long-read data applies verbatim here: SemiBin can be applied, but has not been as extensively tested as for the case of prokaryotics and it is possible (even likely) that parameters may need to be adjusted for this use case.

As above, we are very keen to test SemiBin for these data and ask that, if you have eukaryotic metagenomics data, you feel free to get in touch (shaojun@big-data-biology.org or luispedro@big-data-biology.org).