CLUSTALW

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CLUSTALW

• A Multiple Sequence Alignment Algorithm
• -Prashanth Athri

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Importance

• Essential prelude to Molecular Evolutionary
  Analysis
• Detect conserved sequence regions

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Improvisations

• When comparing sequences.
• - downweight near duplicate sequences
• - upweight divergent ones
• Choice of substitution Matrix is dynamic,depends
  on divergence of sequences
• Variations in Gap penalties

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Algorithm

• The Distance Matrix / Pairwise Alignments
• The Guide tree
• Progressive Alignment

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Distance Matrix

• No. of matches in Best Alignment / No. of
  Comparisons
• Steps to calculate both values

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Distance Matrix
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The Guide Tree

• Use the Distance Matrix and implement a
  Neighborhood Join Method

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Neighbour Join Method

• First Step
• PAM distance 3.3 (Human - Monkey) is the minimum.
  
• Simple average of distances
• DistSpinach,MonHum (DistSpinach, Monkey
  DistSpinach, Human)/2
•                                          
  (90.8 86.3)/2 88.55
• DistRice, MonHum (DistRice, Monkey
  DistRice, Human)/2
•                                        
  (122.4 122.6)/2 122.5
• DistMosquito, MonHum (DistMosquito, Monkey
  DistMosquito, Human)/2
•                                         
  (94.7 80.8)/2 82.75

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Neighbour Join Method
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Intermediate Guide tree
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Final Guide Tree
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Progressive Alignment

• Basic Procedure Use series of pairwise
  Alignments to align larger groups,following the
  Branch Tree.(Leaves to Root)
• Dynamically Aligned at each stage

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Gap Penalties

• Score between a Position in sequence/Alignment to
  a set of other sequences(figure)
• Types
• Initial Gap penalties
• Position Specific Gap penalties

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Gap Penalties

• Gap Opening Penalty (GOP)
• Gap Extension Penalty (GEP)
• Factors affecting GOP
• Dependence on Weight Matrix
• Dependence on similarity of sequences
• Dependence on sequence lengths
• GOP GOP log(MIN(length)) Avg. Residue
  Mismatch
• Percent identity scaling factor

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Gap Penalties

• Factors affecting GEP
• Dependence on difference in lengths of sequences
• GEP GEP(1 log(N/M))
• N,M lengths of two sequences

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Position Specific Gap Penalties

• Lowered Gap Penalties at Existing Gaps(subsequent
  sequences)
• Increased Gap Penalties near existing Gaps(within
  sequence)
• Reduced penalties near Hydrophilic runs

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Progressive Alignment

• The use of different weight Matrices as the
  alignment progresses makes it possible to keep
  from aligning divergent sequences to the end,
  after aligning all the closely related ones.

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