Optimal Sum of Pairs Multiple Sequence Alignment

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Optimal Sum of Pairs Multiple Sequence Alignment

• David Kelley

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Dynamic Programming Extension

• Standard pairwise sequence alignment methods can
  be extended to handle k strings

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But

• Runtime is O(2kNk)
• k of sequences
• N average length of sequences
• Space is O(Nk)
• Quickly becomes unfeasible

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Enter Carillo-Lipman

• Lower bound the score
• Estimate distance from cell to end
• Calculate sum of all pairwise distances from cell
  to end
• If current score estimate lt lower bound
• Ignore that path

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MSA

• Implemented in 1989 program MSA.
• Used a simple progressive alignment procedure to
  obtain a lower bound
• generally can align 6 to 8 sequences of length
  200-300 residues

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Gupta 1995 update

• Re-implemented MSA more efficiently
• Uses a star-tree heuristic for lower bound
• Ran on Sun SparcStation 10 with 128MB of RAM
• Runtimes varied (based on similarity of sequences
  too)
• 10 Globin B proteins of 150 a.a. took 10 min

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Can we do better?

• Better hardware
• more RAM
• multi-core processors
• Better heuristics
• MUSCLE, MAFFT very fast, accurate
• Higher lower bound means more of the matrix can
  be ignored

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My Project

• Implement concepts from Carillo-Lipman
• Use MUSCLE for lower bound
• Look for opportunities to parallelize
• Using openMP
• Run on modern hardware

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Can optimal alignment be made practical?

• How much better can we do than the previous
  attempts?
• How will maximizing sum of pairs compare to more
  popular alignment programs?
• Compare on multiple sequence alignment database,
  BAliBase