<p>This is easy @Laura - I'm a bit surprised by the results Spades meta didn't have a good reputation, but the criteria assessed was not what you are looking for.</p>
<p>Anyway take all outputs and place them in large multi-species alignment,</p>
<ul>
<li>e.g. for each output perform a Blast for maximum genetic diversity for each sequence and sample across the large Blast  output. Take note if there are multiple partial hits against diverse bacteria (online Blast has a diagrammatical summary).</li>
<li>You have a good understanding of your taxonomic group and intersperse that with other stuff, i.e. fill in the diversity.</li>
<li>Assemble it, e.g. muscle5 superfast option.</li>
<li>Perform a split decomposition phylogeny or equivalent which identifies phylogenetic networks.</li>
</ul>
<p><a href="https://uni-tuebingen.de/en/fakultaeten/mathematisch-naturwissenschaftliche-fakultaet/fachbereiche/informatik/lehrstuehle/algorithms-in-bioinformatics/software/splitstree/" rel="nofollow noreferrer">SplitsTree is the historic package</a> for this and it turns out that split decomposition was not the best, I think &quot;neighornet&quot; was superior. What this is does is identify mosaic gene signal in your data. It provides a visual representation. Thus if your data is a artifactual mix of two or more taxa this will cause a network effect between the two parents and your newly mis-assembled sequence will sit between the two in a two &quot;diamond same&quot;. This is the antonym of a bifurcating phylogeny.</p>
<p>The final step is the assembly that produces sequences that minimises phylogenetic networks is the true sequence. If you've not encountered split-decomposition/networks before a verbal explanation might seem confusing but when you run through a few examples and try it on your data you'll get the grasp.</p>

CC BY-SA 4.0
2023-08-28T14:16:53.487Z
Much appreciated! Good idea. Tested. Couldn't see obvious signs of a chimera, but the alignment showed that most of the short 'outlier' sequence's distinguishing features were not present in any other (even distantly related), including a lot of weird Gs. Chimeric with something else maybe? Curious thing is, the depth of that MEGAHIT contig seemed to be pretty good (~120x). I had thought I'd done my homework by quality-controlling the reads with BBDuk, but it's a bit unsettling to see how software can be so certain and so wrong at the same time. Should look more into missassembly detection...
Laura
CC BY-SA 4.0
2023-08-28T14:26:42.100Z
It tentatively sounds like you might have found a new species. Just keep in mind the diversity of bacteria in the analysis affects the ability to detect a possible chimera, i.e. if the "parents" are not present it could throw a false negative -------- Weird "Gs" high AG are a known feature of bacteria: particularly if its genetically distinct. Anyway if Splitstree if done correctly it's a sensitive method for chimeras: but you might have to shift the sample size - remove distant sequences which can cause a collapse in networks.  Megahit is respected BTW.
M__
CC BY-SA 4.0
2023-08-28T14:32:32.923Z
It's more like...The positions in questions are 100% conserved within related bacterial orders, and here's this short sequence with ~9 of these otherwise conserved positions being different. I guess I can't prove it's not real (part of my issue...), but it doesn't look...correct?
Laura
CC BY-SA 4.0
2023-08-28T14:36:45.650Z
What you are saying sounds perfectly reasonable - keep in mind I can't see the data nor analysis. Proof ... it's the first stage requiring downstream analysis, so either leave it as a "putative result" or go into the complexity of metagenome assembly by assembling other single copy gene targets like atpD.
M__
CC BY-SA 4.0
2023-08-28T11:27:23.687Z
2023-08-28T11:40:12.573Z
2023-08-28T11:40:12.573Z
M__
<p>I have a low-diversity metagenome (~11 bins &gt; 80% completion). Out of the bins, 3 are of interest to me. None of the lower-completion bins that can be identified are from the group of interest. So let's call the bins of interest 1, 2 and 3.</p>
<p>The raw reads had been assembled separately with MEGAHIT and SPAdes (meta). Out of them, only the SPAdes assembly was binned / refined. There are 3 16S rRNA in the MEGAHIT assembly (x, y, z) and 3 16S rRNA in the SPAdes assembly (a, b, c).</p>
<p>Bin 1 is associated with sequence 'a', which is identical to 'x'.</p>
<p>Bin 2 is linked with SPAdes sequence 'b', which has no MEGAHIT equivalent. Bin 3 is not associated with any 16S rRNA (even with MarkerMAG).</p>
<p>Sequences 'c' and 'z' are very similar. Sequence 'y' is an outlier.</p>
<p>There are small hints from phylogenetics that bin 3 could be associated with sequences c/z. But then, could sequence 'y' just be a misassembly? Or is it that somehow my final bins are missing an entire genome of interest? If the 16S rRNA for 'y' is real, I would expect a genome divergent enough from the others that it wouldn't get binned together with them. This is what I am trying to understand. Would you happen to have any advice / suggestions on what I could to to test this?</p>
<p>Initial approach: assessing scaffold quality with the BBMap stats.sh . It's a bit difficult to tell, since SPAdes has about 10x more contigs. Worse N50/N90 but more long contigs and a better 'general assembly score'.</p>
<p>Additional thoughts: The new bins seem too divergent from known genomes to use a reference for misassembly estimation.</p>
<p>Thank you for your time!</p>

<phylogenetics><phylogeny><software-recommendation><metagenome><16rrna>
Variation in 16S rRNA between assemblers - how do I know which is real?
# Variation in 16S rRNA between assemblers - how do I know which is real?

(Asked by: username_0 on 2023-08-28)

I have a low-diversity metagenome (~11 bins > 80% completion). Out of the bins, 3 are of interest to me. None of the lower-completion bins that can be identified are from the group of interest. So let's call the bins of interest 1, 2 and 3.

The raw reads had been assembled separately with MEGAHIT and SPAdes (meta). Out of them, only the SPAdes assembly was binned / refined. There are 3 16S rRNA in the MEGAHIT assembly (x, y, z) and 3 16S rRNA in the SPAdes assembly (a, b, c).

Bin 1 is associated with sequence 'a', which is identical to 'x'.

Bin 2 is linked with SPAdes sequence 'b', which has no MEGAHIT equivalent. Bin 3 is not associated with any 16S rRNA (even with MarkerMAG).

Sequences 'c' and 'z' are very similar. Sequence 'y' is an outlier.

There are small hints from phylogenetics that bin 3 could be associated with sequences c/z. But then, could sequence 'y' just be a misassembly? Or is it that somehow my final bins are missing an entire genome of interest? If the 16S rRNA for 'y' is real, I would expect a genome divergent enough from the others that it wouldn't get binned together with them. This is what I am trying to understand. Would you happen to have any advice / suggestions on what I could to to test this?

Initial approach: assessing scaffold quality with the BBMap stats.sh . It's a bit difficult to tell, since SPAdes has about 10x more contigs. Worse N50/N90 but more long contigs and a better 'general assembly score'.

Additional thoughts: The new bins seem too divergent from known genomes to use a reference for misassembly estimation.

Thank you for your time!

**Tags:** phylogenetics, phylogeny, software-recommendation, metagenome, 16rrna

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## 1 answers

### Answer by username_1 on 2023-08-28. Score: 2 | Accepted answer

This is easy @Laura - I'm a bit surprised by the results Spades meta didn't have a good reputation, but the criteria assessed was not what you are looking for.

Anyway take all outputs and place them in large multi-species alignment,

* e.g. for each output perform a Blast for maximum genetic diversity for each sequence and sample across the large Blast output. Take note if there are multiple partial hits against diverse bacteria (online Blast has a diagrammatical summary).
* You have a good understanding of your taxonomic group and intersperse that with other stuff, i.e. fill in the diversity.
* Assemble it, e.g. muscle5 superfast option.
* Perform a split decomposition phylogeny or equivalent which identifies phylogenetic networks.

[SplitsTree is the historic package](https://uni-tuebingen.de/en/fakultaeten/mathematisch-naturwissenschaftliche-fakultaet/fachbereiche/informatik/lehrstuehle/algorithms-in-bioinformatics/software/splitstree/) for this and it turns out that split decomposition was not the best, I think "neighornet" was superior. What this is does is identify mosaic gene signal in your data. It provides a visual representation. Thus if your data is a artifactual mix of two or more taxa this will cause a network effect between the two parents and your newly mis-assembled sequence will sit between the two in a two "diamond same". This is the antonym of a bifurcating phylogeny.

The final step is the assembly that produces sequences that minimises phylogenetic networks is the true sequence. If you've not encountered split-decomposition/networks before a verbal explanation might seem confusing but when you run through a few examples and try it on your data you'll get the grasp.

> **Comments:**
> **username_0**: Much appreciated! Good idea. Tested. Couldn't see obvious signs of a chimera, but the alignment showed that most of the short 'outlier' sequence's distinguishing features were not present in any other (even distantly related), including a lot of weird Gs. Chimeric with something else maybe? Curious thing is, the depth of that MEGAHIT contig seemed to be pretty good (~120x). I had thought I'd done my homework by quality-controlling the reads with BBDuk, but it's a bit unsettling to see how software can be so certain and so wrong at the same time. Should look more into missassembly detection...  
> **username_1**: It tentatively sounds like you might have found a new species. Just keep in mind the diversity of bacteria in the analysis affects the ability to detect a possible chimera, i.e. if the "parents" are not present it could throw a false negative -------- Weird "Gs" high AG are a known feature of bacteria: particularly if its genetically distinct. Anyway if Splitstree if done correctly it's a sensitive method for chimeras: but you might have to shift the sample size - remove distant sequences which can cause a collapse in networks.  Megahit is respected BTW.  
> **username_0**: It's more like...The positions in questions are 100% conserved within related bacterial orders, and here's this short sequence with ~9 of these otherwise conserved positions being different. I guess I can't prove it's not real (part of my issue...), but it doesn't look...correct?  
> **username_1**: What you are saying sounds perfectly reasonable - keep in mind I can't see the data nor analysis. Proof ... it's the first stage requiring downstream analysis, so either leave it as a "putative result" or go into the complexity of metagenome assembly by assembling other single copy gene targets like atpD.  

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