Sequence alignment
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Sequence Alignment. Oct 9, 2002 Joon Lee Genomics & Computational Biology. Dynamic Programming. Optimization problems: find the best decision one after another Subproblems are not independent Subproblems share subsubproblems Solve subproblem, save its answer in a table.

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Sequence Alignment

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Sequence alignment

Sequence Alignment

Oct 9, 2002

Joon Lee

Genomics & Computational Biology


Dynamic programming

Dynamic Programming

  • Optimization problems: find the best decision one after another

  • Subproblems are not independent

  • Subproblems share subsubproblems

  • Solve subproblem, save its answer in a table

Genomics & Computational Biology


Four steps of dp

Four Steps of DP

  • Characterize the structure of an optimal solution

  • Recursively define the value of an optimal solution

  • Compute the value of an optimal solution in a bottom-up fashion

  • Construct an optimal solution from computed information

Genomics & Computational Biology


Sequence alignment1

Sequence Alignment

Sequence 1: G A A T T C A G T T A

Sequence 2: G G A T C G A

Genomics & Computational Biology


Align or insert gap

Align or insert gap

G A A T T C A G T T A

| | | | | |

G G A _ T C _ G _ _ A

G _ A A T T C A G T T A

| | | | | |

G G _ A _ T C _ G _ _ A

Genomics & Computational Biology


Three steps of sa

Three Steps of SA

  • Initialization: gap penalty

  • Scoring: matrix fill

  • Alignment: trace back

Genomics & Computational Biology


Step 1 initialization

Step 1: Initialization

Genomics & Computational Biology


Step 2 scoring

Step 2: Scoring

  • A = a1a2…an, B = b1b2…bm

  • Sij : score at (i,j)

  • s(aibj) : matching score between ai andbj

  • w : gap penalty

figure source

Genomics & Computational Biology


Step 2 scoring1

Step 2: Scoring

  • Match: +2

  • Mismatch: -1

  • Gap: -2

Genomics & Computational Biology


Step 2 scoring2

Step 2: Scoring

0 + 2 = 2

-2 + (-2) = -4

-2 + (-2) = -4

Genomics & Computational Biology


Step 2 scoring3

Step 2: Scoring

-2 + (-1) = -3

-4 + (-2) = -6

2 + (-2) = 0

Genomics & Computational Biology


Step 2 scoring4

Step 2: Scoring

-2 + 2 = 0

2 + (-2) = 0

-4 + (-2) = -6

Genomics & Computational Biology


Step 2 scoring5

Step 2: Scoring

Genomics & Computational Biology


Step 3 trace back

Step 3: Trace back

Genomics & Computational Biology


Step 3 trace back1

Step 3: Trace back

G A A T T C A G T T A

G G A _ T C _ G _ _ A

G A A T T C A G T T A

G G A T _ C _ G _ _ A

Genomics & Computational Biology


Excercise

Excercise

  • Match: +2

  • Mismatch: -1

  • Gap: -2

Genomics & Computational Biology


Excercise1

Excercise

  • Match: +2

  • Mismatch: -1

  • Gap: -2

    G C A T C C G

    G A T C G

    G A T C G

    G A T C G

Genomics & Computational Biology


Amino acids

Amino acids

  • Match/mismatch → Substitution matrix

Genomics & Computational Biology


Global local alignment

Global & Local alignment

  • Global: Needlman-Wunsch Algorithm

  • Local: Smith-Waterman Algorithm

From Mount Bioinformatics Chap 3

Genomics & Computational Biology


References

References

  • Sequence alignment with Java applet

    • http://linneus20.ethz.ch:8080/5_4_5.html

Genomics & Computational Biology


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