<p>My initial reaction is that 21 amino acids is too little information to demonstrate these proteins are homologues (which is the question behind your question). A homologous site means it shares a common ancestry and is distinguishable from random chance or convergent evolution. A common ancestor can be demonstrated using phylogeny (trees).</p>

<p>If a regular alignment program cannot align these sequences, such as clustalo or muscle, the assumption they are homologues cannot be easily tested using phylogeny. That would then become complicated at which point you would need to ask whether it is worth pursing the question.</p>

<p>My recommendation is to perform a simple protein-protein blast and assess the e-scores to get some feel about you data. Your question is achievable, but you would solve this in context to additional sequence data. Whether that sequence data is a denser sample or else contiguous sequence data needs further exploration.</p>

CC BY-SA 4.0
2019-06-03T14:32:22.103Z
2019-06-03T14:32:22.103Z
M__
<p>If you are trying to figure out the proteins' evolutionary history (e.g. if they are homologous) then you want a global alignment. In fact, there are very few cases where a local alignment is better, local is usually done only because it is far more efficient and less computationally expensive than global. But with tiny sequences of just as few residues such as the ones you have, you would want global almost every time.</p>

<p>The only case I can think of where you might prefer local alignment is when you have sequences that share little overall sequence similarity but you suspect they carry some sort of shared motif. For example, in proteins, that could be a protein domain. In that case, you would want to do a local alignment (possibly using something like blast) to identify those sub-regions of higher similarity. </p>

<p>Note that simple sequence similarity isn't really enough for you to decide whether they are indeed homologous. A more sophisticated approach such as <a href="https://blast.ncbi.nlm.nih.gov/Blast.cgi?CMD=Web&amp;PAGE=Proteins&amp;PROGRAM=blastp&amp;RUN_PSIBLAST=on" rel="nofollow noreferrer">psi-blast</a> or <a href="http://hmmer.org/" rel="nofollow noreferrer">HMMER</a> will give better results. Nevertheless, a simple alignment will help you at least discard some obviously non-homologous sequences.</p>

CC BY-SA 4.0
2019-06-03T14:32:50.977Z
2019-06-03T14:32:50.977Z
terdon
<p>As the title says I would like to know which alignment method(global or local) should I use for sequences for which is assumed that they have common ancestry?</p>

<p>The sequences are 21 aa long peptide chains (proteins).</p>

<p>About the background of the sequences, it's only stated that it's ASSUMED that they are from the same ancestry.</p>

<p>The thing that we assume that they are from the same ancestry makes me confused. I know that on similar sequences with the same length usually, we use global.  </p>

CC BY-SA 4.0
2019-06-03T13:21:17.247Z
Depends. What question are you trying to answer? Please [edit] your question and give us some background. Also clarify what kind of sequences you have (nucleotides? protein? genes? cDNA? whole genomes? introns?). How large are your sequences? We can't help if you don't give us more details.
terdon
CC BY-SA 4.0
2019-06-03T13:31:52.603Z
@terdon updated my question with more info. Its more of game with words.. the ancestry states that we should use global but the assume parts gives us idea of using local. Thats the confusing part.
LexByte
CC BY-SA 4.0
2019-06-03T14:00:15.677Z
Thanks for the edit, but you still haven't told us what question you are trying to answer. Why do you want to align them? What information do you want to get from the alignment? Are you trying to see if they are homologous? Are you looking for shared domains?
terdon
CC BY-SA 4.0
2019-06-03T14:06:33.667Z
@terdon I am beginner in this field. I just want to know which is the right method for this. And yeah i would like to test if they really are homologous ( not just assume).
LexByte
CC BY-SA 4.0
2019-06-03T14:33:52.317Z
Thanks, I was asking because the method will depend entirely on the question you are asking :)
terdon
<phylogenetics><multiple-sequence-alignment><sequence-alignment><alignment><alignments>
Global or local alignment on sequences for which it is assumed that they have common ancestry
# Global or local alignment on sequences for which it is assumed that they have common ancestry

(Asked by: username_0 on 2019-06-03)

As the title says I would like to know which alignment method(global or local) should I use for sequences for which is assumed that they have common ancestry?

The sequences are 21 aa long peptide chains (proteins).

About the background of the sequences, it's only stated that it's ASSUMED that they are from the same ancestry.

The thing that we assume that they are from the same ancestry makes me confused. I know that on similar sequences with the same length usually, we use global.

**Tags:** phylogenetics, multiple-sequence-alignment, sequence-alignment, alignment, alignments
> **Comments:**
> **username_1**: Depends. What question are you trying to answer? Please [edit] your question and give us some background. Also clarify what kind of sequences you have (nucleotides? protein? genes? cDNA? whole genomes? introns?). How large are your sequences? We can't help if you don't give us more details.  
> **username_0**: @terdon updated my question with more info. Its more of game with words.. the ancestry states that we should use global but the assume parts gives us idea of using local. Thats the confusing part.  
> **username_1**: Thanks for the edit, but you still haven't told us what question you are trying to answer. Why do you want to align them? What information do you want to get from the alignment? Are you trying to see if they are homologous? Are you looking for shared domains?  
> **username_0**: @terdon I am beginner in this field. I just want to know which is the right method for this. And yeah i would like to test if they really are homologous ( not just assume).  
> **username_1**: Thanks, I was asking because the method will depend entirely on the question you are asking :)  

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## 2 answers

### Answer by username_2 on 2019-06-03. Score: 1

My initial reaction is that 21 amino acids is too little information to demonstrate these proteins are homologues (which is the question behind your question). A homologous site means it shares a common ancestry and is distinguishable from random chance or convergent evolution. A common ancestor can be demonstrated using phylogeny (trees).

If a regular alignment program cannot align these sequences, such as clustalo or muscle, the assumption they are homologues cannot be easily tested using phylogeny. That would then become complicated at which point you would need to ask whether it is worth pursing the question.

My recommendation is to perform a simple protein-protein blast and assess the e-scores to get some feel about you data. Your question is achievable, but you would solve this in context to additional sequence data. Whether that sequence data is a denser sample or else contiguous sequence data needs further exploration.


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### Answer by username_1 on 2019-06-03. Score: 1

If you are trying to figure out the proteins' evolutionary history (e.g. if they are homologous) then you want a global alignment. In fact, there are very few cases where a local alignment is better, local is usually done only because it is far more efficient and less computationally expensive than global. But with tiny sequences of just as few residues such as the ones you have, you would want global almost every time.

The only case I can think of where you might prefer local alignment is when you have sequences that share little overall sequence similarity but you suspect they carry some sort of shared motif. For example, in proteins, that could be a protein domain. In that case, you would want to do a local alignment (possibly using something like blast) to identify those sub-regions of higher similarity.

Note that simple sequence similarity isn't really enough for you to decide whether they are indeed homologous. A more sophisticated approach such as [psi-blast](https://blast.ncbi.nlm.nih.gov/Blast.cgi?CMD=Web&PAGE=Proteins&PROGRAM=blastp&RUN_PSIBLAST=on) or [HMMER](http://hmmer.org/) will give better results. Nevertheless, a simple alignment will help you at least discard some obviously non-homologous sequences.


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