Compare sequence alignments of datasets

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Raffael
Raffael 2016-9-21
编辑： Luuk van Oosten 2016-9-21
Hi I have several Fasta files with the sequence of multiple versions of a gene from different species. So 1 File per gene with 10 entrys (because I have 10 genomes). I wan’t to compare do an alignment of each gene and then compare those alignment so see if the behave the same (species A is in all genes related to species B). Do you know some features for Matlab how i can compare alignemnts?
Best Raffael

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回答（2 个）

Luuk van Oosten
Luuk van Oosten 2016-9-21
Dear Raffael,
This is possible in MATLAB. I suggest you have a look at this page.
If you want to know more on how to work with FASTA files, you might want to have a look over here.
All these functions are part of the Bioinformatics toolbox.
Raffael
Raffael 2016-9-21
Dear Luuk
Thanks for you reply. Unfortunately, I can not find any tool that would solve my problem.
Lets say I have two alignments Alignment 1: with Gene A for 10 species Alignment 2: with Gene B for 10 species
I want to compare those two alignments to see if the species within the alignment are clustered in the same way
Any idea how to do this?
  1 个评论
Luuk van Oosten
Luuk van Oosten 2016-9-21
编辑：Luuk van Oosten 2016-9-21
So you want to build some kind of phylogenetic tree based on the similarity given by the multiple sequence alignment?
If this is the case, then YES you can do this kind of stuff in MATLAB. I suggest having a look over here in the section on building phylogenetic trees.
A simple example (might not be EXACTLY) what you are looking for, but it is a start (note: this comes from the documentation):
% take the p53 sample data
p53 = fastaread('p53samples.txt')
% Compute the pairwise distances between each pair of sequences using the 'GONNET' scoring matrix.
% You can take any of the other scoring matrices as well, depends on your task.
dist = seqpdist(p53,'ScoringMatrix','GONNET');
% Build a phylogenetic tree using an unweighted average distance (UPGMA) method
tree = seqlinkage(dist,'average',p53)
% Perform progressive alignment using the PAM family scoring matrices.
ma = multialign(p53,tree,'ScoringMatrix',...
{'pam150','pam200','pam250'})
% show the alignment
showalignment(ma)
% Show that tree of the allignment
h = plot(tree)
Best regards

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