Difference between revisions of "BIN-ALI-Similarity"

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Measuring Sequence Similarity
 
Measuring Sequence Similarity
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(sequence similarity: measurement via MDM; BLOSUM 62 matrix, affine gap penalties)
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<b>Keywords:</b>&nbsp;
 
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sequence similarity: measurement via MDM; BLOSUM 62 matrix, affine gap penalties
 
 
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<b>Abstract:</b><br />
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== Abstract ==
 
 
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<!-- included from "./components/BIN-ALI-Similarity.components.txt", section: "abstract" -->
 
 
In order to compare protein sequences quantitatively, we must define how to measure the similarity of two amino acids. This can be done according to biophysical considerations, or empirically, based on the propensity of amino acids to substitute for each other in homologous sequences. "Mutation Data Matrices" make this information conveniently available.
 
In order to compare protein sequences quantitatively, we must define how to measure the similarity of two amino acids. This can be done according to biophysical considerations, or empirically, based on the propensity of amino acids to substitute for each other in homologous sequences. "Mutation Data Matrices" make this information conveniently available.
 
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== This unit ... ==
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=== Prerequisites ===
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<b>Objectives:</b><br />
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You need to complete the following units before beginning this one:
 
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*[[RPR-Biostrings|RPR-Biostrings (The biostrings R Package)]]
 
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=== Objectives ===
 
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This unit will ...
 
This unit will ...
 
* ... introduce issues of defining amino acid similarity;
 
* ... introduce issues of defining amino acid similarity;
 
* ... teach how to use the amino acid property tables from the seqinr package;
 
* ... teach how to use the amino acid property tables from the seqinr package;
 
* ... teach the use of mutation data matrices from the Biostrings package.
 
* ... teach the use of mutation data matrices from the Biostrings package.
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<b>Outcomes:</b><br />
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=== Outcomes ===
 
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After working through this unit you ...
 
After working through this unit you ...
 
* ... can access and work with amino acid property tables from the seqinr package;
 
* ... can access and work with amino acid property tables from the seqinr package;
 
* ... can access and work with mutation data matrices from the Biostrings package, in particular BLOSUM62.
 
* ... can access and work with mutation data matrices from the Biostrings package, in particular BLOSUM62.
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*<b>Time management</b>: Before you begin, estimate how long it will take you to complete this unit. Then, record in your course journal: the number of hours you estimated, the number of hours you worked on the unit, and the amount of time that passed between start and completion of this unit.
 
*<b>Time management</b>: Before you begin, estimate how long it will take you to complete this unit. Then, record in your course journal: the number of hours you estimated, the number of hours you worked on the unit, and the amount of time that passed between start and completion of this unit.
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*<b>Insights</b>: If you find something particularly noteworthy about this unit, make a note in your [[ABC-Insights|'''insights!''' page]].
 
*<b>Insights</b>: If you find something particularly noteworthy about this unit, make a note in your [[ABC-Insights|'''insights!''' page]].
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<section begin=prerequisites />
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<b>Prerequisites:</b><br />
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<!-- included from "./data/ABC-unit_components.txt", section: "notes-prerequisites" -->
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This unit builds on material covered in the following prerequisite units:
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*[[RPR-Biostrings|RPR-Biostrings (The biostrings R Package)]]
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== Contents ==
 
== Contents ==
 
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== Further reading, links and resources ==
 
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*{{#pmid: 15286655}}
 
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*{{WP|BLOSUM|'''BLOSUM''' article at Wikipedia}} (Good article.)
 
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== Notes ==
 
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== Self-evaluation ==
 
== Self-evaluation ==
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=== Question 1===
 
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== Further reading, links and resources ==
  
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*{{#pmid: 15286655}}
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*{{WP|BLOSUM|'''BLOSUM''' article at Wikipedia}} (Good article.)
  
  

Revision as of 19:31, 26 January 2018

Measuring Sequence Similarity

(sequence similarity: measurement via MDM; BLOSUM 62 matrix, affine gap penalties)


 


Abstract:

In order to compare protein sequences quantitatively, we must define how to measure the similarity of two amino acids. This can be done according to biophysical considerations, or empirically, based on the propensity of amino acids to substitute for each other in homologous sequences. "Mutation Data Matrices" make this information conveniently available.

Objectives:
This unit will ...

  • ... introduce issues of defining amino acid similarity;
  • ... teach how to use the amino acid property tables from the seqinr package;
  • ... teach the use of mutation data matrices from the Biostrings package.

Outcomes:
After working through this unit you ...

  • ... can access and work with amino acid property tables from the seqinr package;
  • ... can access and work with mutation data matrices from the Biostrings package, in particular BLOSUM62.

Deliverables:

  • Time management: Before you begin, estimate how long it will take you to complete this unit. Then, record in your course journal: the number of hours you estimated, the number of hours you worked on the unit, and the amount of time that passed between start and completion of this unit.
  • Journal: Document your progress in your Course Journal. Some tasks may ask you to include specific items in your journal. Don't overlook these.
  • Insights: If you find something particularly noteworthy about this unit, make a note in your insights! page.

Prerequisites:
This unit builds on material covered in the following prerequisite units:


 



 



 


Contents

Task:


 

The NCBI makes its alignment matrices available by ftp. They are located at ftp://ftp.ncbi.nih.gov/blast/matrices - for example here is a link to the BLOSUM62 matrix[1]. 

BLOSUM62

   A  R  N  D  C  Q  E  G  H  I  L  K  M  F  P  S  T  W  Y  V  B  J  Z  X  *
A  4 -1 -2 -2  0 -1 -1  0 -2 -1 -1 -1 -1 -2 -1  1  0 -3 -2  0 -2 -1 -1 -1 -4
R -1  5  0 -2 -3  1  0 -2  0 -3 -2  2 -1 -3 -2 -1 -1 -3 -2 -3 -1 -2  0 -1 -4
N -2  0  6  1 -3  0  0  0  1 -3 -3  0 -2 -3 -2  1  0 -4 -2 -3  4 -3  0 -1 -4
D -2 -2  1  6 -3  0  2 -1 -1 -3 -4 -1 -3 -3 -1  0 -1 -4 -3 -3  4 -3  1 -1 -4
C  0 -3 -3 -3  9 -3 -4 -3 -3 -1 -1 -3 -1 -2 -3 -1 -1 -2 -2 -1 -3 -1 -3 -1 -4
Q -1  1  0  0 -3  5  2 -2  0 -3 -2  1  0 -3 -1  0 -1 -2 -1 -2  0 -2  4 -1 -4
E -1  0  0  2 -4  2  5 -2  0 -3 -3  1 -2 -3 -1  0 -1 -3 -2 -2  1 -3  4 -1 -4
G  0 -2  0 -1 -3 -2 -2  6 -2 -4 -4 -2 -3 -3 -2  0 -2 -2 -3 -3 -1 -4 -2 -1 -4
H -2  0  1 -1 -3  0  0 -2  8 -3 -3 -1 -2 -1 -2 -1 -2 -2  2 -3  0 -3  0 -1 -4
I -1 -3 -3 -3 -1 -3 -3 -4 -3  4  2 -3  1  0 -3 -2 -1 -3 -1  3 -3  3 -3 -1 -4
L -1 -2 -3 -4 -1 -2 -3 -4 -3  2  4 -2  2  0 -3 -2 -1 -2 -1  1 -4  3 -3 -1 -4
K -1  2  0 -1 -3  1  1 -2 -1 -3 -2  5 -1 -3 -1  0 -1 -3 -2 -2  0 -3  1 -1 -4
M -1 -1 -2 -3 -1  0 -2 -3 -2  1  2 -1  5  0 -2 -1 -1 -1 -1  1 -3  2 -1 -1 -4
F -2 -3 -3 -3 -2 -3 -3 -3 -1  0  0 -3  0  6 -4 -2 -2  1  3 -1 -3  0 -3 -1 -4
P -1 -2 -2 -1 -3 -1 -1 -2 -2 -3 -3 -1 -2 -4  7 -1 -1 -4 -3 -2 -2 -3 -1 -1 -4
S  1 -1  1  0 -1  0  0  0 -1 -2 -2  0 -1 -2 -1  4  1 -3 -2 -2  0 -2  0 -1 -4
T  0 -1  0 -1 -1 -1 -1 -2 -2 -1 -1 -1 -1 -2 -1  1  5 -2 -2  0 -1 -1 -1 -1 -4
W -3 -3 -4 -4 -2 -2 -3 -2 -2 -3 -2 -3 -1  1 -4 -3 -2 11  2 -3 -4 -2 -2 -1 -4
Y -2 -2 -2 -3 -2 -1 -2 -3  2 -1 -1 -2 -1  3 -3 -2 -2  2  7 -1 -3 -1 -2 -1 -4
V  0 -3 -3 -3 -1 -2 -2 -3 -3  3  1 -2  1 -1 -2 -2  0 -3 -1  4 -3  2 -2 -1 -4
B -2 -1  4  4 -3  0  1 -1  0 -3 -4  0 -3 -3 -2  0 -1 -4 -3 -3  4 -3  0 -1 -4
J -1 -2 -3 -3 -1 -2 -3 -4 -3  3  3 -3  2  0 -3 -2 -1 -2 -1  2 -3  3 -3 -1 -4
Z -1  0  0  1 -3  4  4 -2  0 -3 -3  1 -1 -3 -1  0 -1 -2 -2 -2  0 -3  4 -1 -4
X -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -4
* -4 -4 -4 -4 -4 -4 -4 -4 -4 -4 -4 -4 -4 -4 -4 -4 -4 -4 -4 -4 -4 -4 -4 -4  1


Task:

  • Study this and make sure you understand what this table is, how it can be used, and what a reasonable range of values for identities and pairscores for non-identical, similar and dissimilar residues is. Ask on the mailing list in case you have questions. This piece of data is the foundation of any sequence alignment. without it, no sensible alignment could be produced!
  • Figure out the following values:
    • Compare an identical match of histidine with an identical match of serine. What does this mean?
    • How similar are lysine and leucine, as compared to leucine and isoleucine? Is this what you expect?
    • PAM matrices are sensitive to an interesting artefact. Since W and R can be interchanged with a single point mutation, the probability of observing W→R and R→W exchanges in closely related sequences is much higher than one would expect from the two amino acid's biophysical properties. (Why?) PAM matrices were compiled from hypothetical point exchanges and then extrapolated. Therefore these matrices assign a relatively high degree of similarity to (W, R), that is not warranted considering what actually happens in nature. Do you see this problem in the BLOSUM matrix? If BLOSUM does not have this issue, why not?


 

Template:ABC-Unit


 

Self-evaluation

Notes

  1. ↑ That directory also contains sourcecode to generate the PAM matrices. This may be of interest if you ever want to produce scoring matrices from your own datasets.

Further reading, links and resources

  • Eddy (2004) Where did the BLOSUM62 alignment score matrix come from?. Nat Biotechnol 22:1035-6. (pmid: 15286655)

    [ PubMed ] [ DOI ] Many sequence alignment programs use the BLOSUM62 score matrix to score pairs of aligned residues. Where did BLOSUM62 come from?


     



     

    If in doubt, ask! If anything about this learning unit is not clear to you, do not proceed blindly but ask for clarification. Post your question on the course mailing list: others are likely to have similar problems. Or send an email to your instructor.


     

    About ...
     
    Author:

    Boris Steipe <boris.steipe@utoronto.ca>

    Created:

    2017-08-05

    Modified:

    2017-10-20

    Version:

    1.0

    Version history:

    • 1.0 First live version
    • 0.1 First stub

    CreativeCommonsBy.png This copyrighted material is licensed under a Creative Commons Attribution 4.0 International License. Follow the link to learn more.

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