Multiple Sequence Alignment by Iterative Tree-Neighbor Alignments

1
Multiple Sequence Alignment by Iterative
Tree-Neighbor Alignments

• Susan Bibeault
• June 9, 2000

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Outline

• Problem Statement and Importance
• Terminology
• Current Approaches
• Our Alignment Heuristic
• Performance Results
• Conclusions
• Future Work

3
Outline

• Problem Statement and Importance
• Terminology
• Current Approaches
• Our Alignment Heuristic
• Performance Results
• Conclusions
• Future Work

4
Multiple Sequence Alignment

• Problem
• Given Sequence Set
• Insert gaps into sequences
• so that evolutionary conserved regions are
  aligned
• Important tool
• Relate Homologous Proteins
• Discover Conserved Regions

VLSPADNVKAAWGKVGAHAGEYGAEALERMF VHLTPEEKSAVTALWGKV
NVDEVGGEALGRLLVVY GLSDGEWQLVLNVWGKVEADIPGHVLIRLFK
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Outline

• Problem Statement and Importance
• Terminology
• Current Approaches
• Our Alignment Heuristic
• Performance Results
• Conclusions
• Future Work

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Scoring Multiple Alignments
? cost(i,j) 6
? cost(edge) 1 m
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Alignments

• Scoring
• Cost Matrix
• C (aa1, aa2)
• Gaps Penalties
• Simple
• C (aa, -)
• Affine
• C(-) Len C (aa,-)

V
L
S
P
A
D
N
V
K
A
G
L
S
D
G
E
W
Q
L
V
L
Cost(s1..i,ti..j) min(
Cost(s1..i,ti..j-1) g,
Cost(s1..i-1,ti..j-1) C(si,tj)
Cost(s1..i-1,ti..j) g))
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Outline

• Problem Statement and Importance
• Terminology
• Current Approaches
• Our Alignment Heuristic
• Performance Results
• Conclusions
• Future Work

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Current Approaches

• Global Methods
• Optimal Algorithms (MSA, MWT, MUSEQAL)
• Progressive (MULTALIGN, PILEUP, CLUSTAL, MULTAL,
  AMULT, DFALIGN, MAP, PRRP, AMPS)
• Local methods
• PIMA, DIALIGN, PRALIGN, MACAW, BlockMaker,
  Iteralign
• Combined (GENALIGN, ASSEMBLE, DCA)
• Statistical (HMMT, SAGA, SAM, Match Box)
• Parsimony (MALIGN, TreeAlign)

Global Alignment ABCDEFGHI
ABCD-FGHI Local Alignment XXXABCDYYY ZZZ
ABCDEEEE

• Global Methods
• Optimal Algorithms (MSA, MWT, MUSEQAL)
• Progressive (MULTALIGN, PILEUP, CLUSTAL, MULTAL,
  AMULT, DFALIGN, MAP, PRRP, AMPS)
• Local methods
• PIMA, DIALIGN, PRALIGN, MACAW, BlockMaker,
  Iteralign
• Combined (GENALIGN, ASSEMBLE, DCA)
• Statistical (HMMT, SAGA, SAM, Match Box)
• Parsimony (MALIGN, TreeAlign)

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Outline

• Problem Statement and Importance
• Terminology
• Current Approaches
• Our Alignment Heuristic
• Performance Results
• Conclusions
• Future Work

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Our Heuristic

• Distance Estimation
• Tree Construction
• Node Initialization
• Tree Partitioning
• Iteration

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Estimation of Protein Distance

• Aligned Sequences Estimated Pair Distances
• Issue Implied vs. Optimal Pair Alignments

PEAAALYGRFT---IKSDVW PESAALYGRFT---IKSDVW PESLALYN
KF---SIKSDVW PEALNYGRY----SSESDVW PEALNYGWY----SSE
SDVW PEVIRMQDDNPFSFSQSDVY
PEALNYGWY----SSESDVW PEVIRMQDDNPFSFSQSDVY
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Optimal Pair vs. Implied Pair
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Interior Node Classification

• Interior Nodes Classified by Percent Identity
• PID ( matched residues) / ( total residues)
• User Specified Tiers
• User Specified Cost Criterion
• Example
• PID gt 60 -- PAM 40 High Gap Penalties
• PID gt 40 -- PAM 120 Medium Gap Penalties
• PID lt 40 -- PAM 200 Low Gap Penalty

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Ordering Alignments

• Isolate Sub Trees
• Threshold PID
• Order Alignments
• Sub Tree
• Border Nodes
• Integrate All

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Interior Alignments

• Sum of Pairs
• Bounded Search
• Implementation
• Modular
• Reentrant
• Flexible Cost Criterion

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Generating Consensus

• Alignment (A1,A2,A3)
• Consensus X
• Min (? Di(Ai,X) )
• For Each Position i
• Xi ? ?

A1
D1
D2
X
A2
D3
A3
Min (cost(?, A1i) cost(?, A2i) cost(?, A3i))
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Outline

• Problem Statement and Importance
• Terminology
• Current Approaches
• Our Alignment Heuristic
• Performance Results
• Conclusions
• Future Work

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Testing the Method

• BAliBASE benchmark
• Correct Alignments
• Core Blocks of Conserved Motifs
• Typical Hard Problem Sets
• Protein Parsimony
• Measures Evolutionary Steps of Alignment

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Baseline BAliBASE SP
better
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Baseline BAliBASE TC
better
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Baseline - ProtPars
better
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Orphans/Families BAliBASE SP
better
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Orphans/Families ProtPars
better
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Larger Families
better
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Outline

• Problem Statement and Importance
• Terminology
• Current Approaches
• Our Alignment Heuristic
• Performance Results
• Conclusions
• Future Work

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Conclusions

• Solution Quality
• Captures Evolutionary Information
• Iterations Converge Quickly
• Useful Tool

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Outline

• Problem Statement and Importance
• Terminology
• Current Approaches
• Our Alignment Heuristic
• Performance Results
• Conclusions
• Future Work

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Future Work

• Improved Alignment Consensus
• Multiple Partitioning Thresholds
• Multiple Solutions
• Integrated Phylogeny Modifications
• Parallel Implementation