de novo metagenomics on viral NGS data is a hot-topic. On this site alone at least 4 specific algorithms have been used to identify multi-strain/multi-species for a given data set, however these do not necessarily involve short-read data, and are listed below.
Questions What approach is recommended for traditional Illumina multiple infection data both for:
- for intraspecific (intra-species) data; and
- for different species co-infecting the patient, but within the same virus family?
- Benchmarking using a common standard (for example)
- Error rates, not miscalling a SNP but producing mosaic artefacts (an artificially mixed genome)
- Suitability of short-read data for intra-species metagenomics.
Programs discussed on Bioinformatics SE:
SAVAGE https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5411778/ Baaijens et al. De novo assembly of viral quasispecies using overlap graphs Genome Research 2017 May; 27: 835–848.
S-aligner (@juanjo75es) https://www.biorxiv.org/content/biorxiv/early/2021/02/02/2021.02.02.429443.full.pdf Juanjo Bermúdez s-aligner: a greedy algorithm for non-greedy de novo genome assembly 2021 bioRχiv February: 1-7
Rey http://denovoassembler.sourceforge.net Sébastien Boisvert et al Genome Biology. 2012 13:R122, December
@LRJoshi here used the Broad Viral NGS pipeline for de novo assembly. https://viral-ngs.readthedocs.io/en/latest/assembly.html
These are very small genomes < 30 kb. Quasi-species is a very real phenomenon (loads of mutations), however mixed infections are also well-known. In a mixed infection, producing one genome which is a mix of two genetically distinct viruses is a key concern.