<p>It is likely the sequence data in this instance, the more sequences the more chance an issue with the alignment where variations in the gap penalty are observed.</p>
<p>MAFFT outperforms Clustal Omega to some extent over significantly larger alignments &gt;50 000 sequences from published benchmark studies (FAMSA paper), but this is not relevant here.</p>

CC BY-SA 4.0
2022-03-07T23:54:11.833Z
2022-03-07T23:54:11.833Z
M__
<p>The length of the alignment will depend on the model. For example, high gap costs will typically result in shorter alignments, whereas low gap-costs will do the opposite.</p>
<p>Consider the sequences below:</p>
<pre><code>AAAAA
TTTTT
GGGGG
</code></pre>
<p>with a very large gap cost, these sequences will result in the following MSA</p>
<pre><code>AAAAA
|||||
TTTTT
|||||
GGGGG
</code></pre>
<p>but with lower gap costs, we'd observe</p>
<pre><code>AAAAA----------
-----TTTTT-----
----------GGGGG
</code></pre>
<p>Of course, this is an extreme case, but it goes to show that the alignment model will vary how long the resulting alignment is.</p>

CC BY-SA 4.0
2021-10-08T22:41:14.123Z
I noticed also one thing when the input (length of sequences)  before the MSA method are on the same length, the output after alignment methods are all on equal length, however, when the input differs, the output differs as well. Is it right?
Radwa Elawadi
CC BY-SA 4.0
2021-10-09T01:27:53.940Z
For a single run of MSA on a set of sequences, the output lengths should all be the same, regardless of input length.
Throckmorton
CC BY-SA 4.0
2021-10-08T17:49:44.317Z
2022-03-08T17:13:53.603Z
2022-03-08T17:13:53.603Z
Throckmorton
<p>I applied three multiple sequence alignment methods of muscle, mafft and clistal omega on 30 sequences and 400 sequences . In the case of 30 seq, the output of alignment from the 3 methods was in the same length but in the case of larger data with different length of sequences (input data) the output from alignment methods was different length clustal length is different than the two others. My question is how can i assure that the length from MSA should be equal or different?</p>

<variation><multiple-sequence-alignment>
Multiple Sequence Alignment
# Multiple Sequence Alignment

(Asked by: username_0 on 2021-10-07)

I applied three multiple sequence alignment methods of muscle, mafft and clistal omega on 30 sequences and 400 sequences . In the case of 30 seq, the output of alignment from the 3 methods was in the same length but in the case of larger data with different length of sequences (input data) the output from alignment methods was different length clustal length is different than the two others. My question is how can i assure that the length from MSA should be equal or different?

**Tags:** variation, multiple-sequence-alignment

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## 2 answers

### Answer by username_1 on 2022-03-07. Score: 1

It is likely the sequence data in this instance, the more sequences the more chance an issue with the alignment where variations in the gap penalty are observed.

MAFFT outperforms Clustal Omega to some extent over significantly larger alignments >50 000 sequences from published benchmark studies (FAMSA paper), but this is not relevant here.


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### Answer by username_2 on 2021-10-08. Score: 1

The length of the alignment will depend on the model. For example, high gap costs will typically result in shorter alignments, whereas low gap-costs will do the opposite.
Consider the sequences below:
AAAAA
TTTTT
GGGGG

with a very large gap cost, these sequences will result in the following MSA
AAAAA
|||||
TTTTT
|||||
GGGGG

but with lower gap costs, we'd observe
AAAAA----------
-----TTTTT-----
----------GGGGG

Of course, this is an extreme case, but it goes to show that the alignment model will vary how long the resulting alignment is.

> **Comments:**
> **username_0**: I noticed also one thing when the input (length of sequences)  before the MSA method are on the same length, the output after alignment methods are all on equal length, however, when the input differs, the output differs as well. Is it right?  
> **username_2**: For a single run of MSA on a set of sequences, the output lengths should all be the same, regardless of input length.  

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