Answers.Body: <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>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2023-08-28T14:16:53.487Z
Answers.Text: 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...
Answers.UserDisplayName: Laura
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Answers.CreationDate: 2023-08-28T14:26:42.100Z
Answers.Text: 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.
Answers.UserDisplayName: M__
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Answers.CreationDate: 2023-08-28T14:32:32.923Z
Answers.Text: 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?
Answers.UserDisplayName: Laura
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2023-08-28T14:36:45.650Z
Answers.Text: 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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Body: <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>
  
Tags: <phylogenetics><phylogeny><software-recommendation><metagenome><16rrna>
Title: Variation in 16S rRNA between assemblers - how do I know which is real?
ThreadText: # 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
  
  
  ---
  
  ## 1 answers
  
  ### Answer by username_1 on 2023-08-28. Score: 2 | Accepted answer
  
  This is easy @username_0 - 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.  
  
  ---
  
  