Global Alignment algorithm with example and applications

1. GLOBAL ALIGNMENT
Pinky Sheetal V
M.tech Bioinformatics

2. CONTENTS
 Sequence Alignment
 Dynamic Programming Algorithm
 Global Alignment

3. The result of inserting gaps into the strings such that
afterwards as many positions as possible coincides.
X: AGGCTATCA
Y: TAGCTATCA

4. Scoring weights:
For a match : +m
For a mismatch : -s
For a gap : -d
Alignment Score:
F = (# matches) x m - (# mismatches) x s – (#gaps) x d

5. Complex Problem
Sub prob1
Soln 1 Sub prob2
Sub prob3
Soln 2
Soln 3

6. GLOBAL ALIGNMENT

7. •Allows obtaining the optimal alignment with linear gap cost has
been proposed by Needleman and Wunsch by providing a
score, for each position of the aligned sequences.
•Based on the dynamic programming technique.
•For two sequences of length m and n we define a matrix of
dimensions m+1 and n+1.

8. Termination Condition:
Optimal score between the two sequences
obtained at the last cell of the last row and last
column.

9. Sequences:
S: ATTATCT
T: TTTCTA
T
S 0 _ T T T C T A
_ 0 -1 -2 -3 -4 -5 -6
A -1 0 -1 -2 -3 -4 -5
T -2 1 2 1 0 -1 -2
T -3 0 3 4 3 2 1
A -4 -1 2 3 4 3 4 Match Score = +2
Mismatch Score = 0
T -5 -2 1 4 3 6 5
Gap Penalty = -1
C -6 -3 0 3 6 5 6
T -7 -4 -1 2 5 8 7

10. T
0 _ T T T C T A
S
_ 0 -1 -2 -3 -4 -5 -6
A -1 0 -1 -2 -3 -4 -5
T -2 1 2 1 0 -1 -2
T -3 0 3 4 3 2 1
A -4 -1 2 3 4 3 4
T -5 -2 1 4 3 6 5
C -6 -3 0 3 6 5 6
T -7 -4 -1 2 5 8 7

11.  Optimal Alignment:
S
ATTATC T–
T - TT – TC TA
No: of matches = 5
No: of mismatches = 3
(5 x 2) – (3 x -1) = 7

12. Tools that utilize Global Alignment Algorithm
 EMBOSS Needle
 EMBOSS Stretcher
Applications:
 Identify Conserved Interaction Pathways and Complexes [Brian P.
Kelley,et al.2003]
 Functional Orthology Detection [ Rohit Singh.et al.2008]
Advantages:
The similar sequence region is of the same order and orientation.
Disadvantage:
Slow, Memory Intensive
Cannot be applied on genome-sized sequences