<p>I would suggest first using a binning approach such as <a href="https://bitbucket.org/berkeleylab/metabat" rel="nofollow noreferrer">MetaBAT2</a> (or an equivalent tool, there are many) to separate your metagenomic assembly into bins roughly corresponding to genomes. I would then run <a href="https://ecogenomics.github.io/CheckM/#:%7E:text=CheckM%20provides%20a%20set%20of,copy%20within%20a%20phylogenetic%20lineage." rel="nofollow noreferrer">CheckM</a> to assess the bins' quality/completeness/purity.</p>
<p>If you still want to use quast, you could then run metaquast with a reference genome appropriate to each bin independently. I would suggest <a href="https://academic.oup.com/bioinformatics/article/36/6/1925/5626182" rel="nofollow noreferrer">GTDB-tk</a> to perform a classification and identify such an appropriate reference genome.</p>

CC BY-SA 4.0
2022-07-26T21:19:56.523Z
Thanks @MaximilianPress good way to take the question forward
M__
CC BY-SA 4.0
2022-07-27T14:05:13.720Z
Thank you @MaximilianPress, I received a similar answer at Reddit, so I believe this might be a better way to proceed indeed
Poccia
CC BY-SA 4.0
2022-07-26T20:29:31.980Z
2022-07-26T20:29:31.980Z
Maximilian Press
<p>I'm working with whole genome metagenomic samples from human skin, and I'm using MEGAHIT for assembly and MetaQuast for evaluation. However, MetaQuast requires a list of reference genomes for the analysis (if I understood correctly). When I perform the evaluation without the references, it uses BLASTN for aligning contigs to SILVA 16S rRNA database. Since I'm working with whole genome sequences, this is not an optimal choice. As expected, MetaQuast is identifying only two species in my contigs file, although I have manually checked through BLASTN that there are contigs that match other species' genomes. And this evaluation makes my assembly looks terrible. Since I'm working with samples from human skin, it wouldn't be viable to download a database of reference genomes and perform MetaQuast using a local alignment. So, what would be the best approach to perform the evaluation correctly in my case?</p>
<p>Looking forward to discussing it!</p>

<assembly><metagenome><wgs>
MetaQuast for assembling samples from complex communities
# MetaQuast for assembling samples from complex communities

(Asked by: username_0 on 2022-07-26)

I'm working with whole genome metagenomic samples from human skin, and I'm using MEGAHIT for assembly and MetaQuast for evaluation. However, MetaQuast requires a list of reference genomes for the analysis (if I understood correctly). When I perform the evaluation without the references, it uses BLASTN for aligning contigs to SILVA 16S rRNA database. Since I'm working with whole genome sequences, this is not an optimal choice. As expected, MetaQuast is identifying only two species in my contigs file, although I have manually checked through BLASTN that there are contigs that match other species' genomes. And this evaluation makes my assembly looks terrible. Since I'm working with samples from human skin, it wouldn't be viable to download a database of reference genomes and perform MetaQuast using a local alignment. So, what would be the best approach to perform the evaluation correctly in my case?

Looking forward to discussing it!

**Tags:** assembly, metagenome, wgs

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## 1 answers

### Answer by username_1 on 2022-07-26. Score: 1 | Accepted answer

I would suggest first using a binning approach such as [MetaBAT2](https://bitbucket.org/berkeleylab/metabat) (or an equivalent tool, there are many) to separate your metagenomic assembly into bins roughly corresponding to genomes. I would then run [CheckM](https://ecogenomics.github.io/CheckM/#:%7E:text=CheckM%20provides%20a%20set%20of,copy%20within%20a%20phylogenetic%20lineage.) to assess the bins' quality/completeness/purity.

If you still want to use quast, you could then run metaquast with a reference genome appropriate to each bin independently. I would suggest [GTDB-tk](https://academic.oup.com/bioinformatics/article/36/6/1925/5626182) to perform a classification and identify such an appropriate reference genome.

> **Comments:**
> **username_2**: Thanks @MaximilianPress good way to take the question forward  
> **username_0**: Thank you @MaximilianPress, I received a similar answer at Reddit, so I believe this might be a better way to proceed indeed  

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