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In a previous paper, we introduced MUSCLE, a new program for creating multiple alignments of protein sequences, giving a brief summary of the algorithm and showing MUSCLE to achieve the highest scores reported to date on four alignment accuracy benchmarks

Robert C Edgar

2004

Scholarcy highlights

  • In a previous paper, we introduced MUSCLE, a new program for creating multiple alignments of protein sequences, giving a brief summary of the algorithm and showing MUSCLE to achieve the highest scores reported to date on four alignment accuracy benchmarks
  • Two attributes of multiple sequence alignment programs are of primary importance to the user: biological accuracy and computational complexity
  • We report speed and accuracy results for three sets of options: the full MUSCLE algorithm including Stages 1, 2 and 3 with default options; Stages 1 and 2 only, using default options; and Stage 1 only using the fastest possible options, which are as follows: FBinary is used as a distance measure, the profile sum of pairs profile function is used, and diagonal finding is enabled
  • Alignment accuracy In Tables 3 and 4 we report the speed and accuracy of MUSCLE v3.3, CLUSTALW v1.82, Progressive POA, a recently published method that is claimed to be 10 to 30 times faster than CLUSTALW for large alignments, and the MAFFT script FFTNS1 v3.82, the fastest previously published method known to us
  • We have previously shown that MUSCLE-prog is faster than FFTNS1 on a set of 5,000 sequences, for which we estimated that CLUSTALW would require approximately one year
  • While the design–typically for practical multiple sequence alignment tools–arguably lacks elegance and theoretical coherence, useful improvements were achieved through a number of factors
  • MUSCLE enables high-throughput applications to achieve average accuracy comparable to the most accurate tools previously available, which we expect to be increasingly important in view of the continuing rapid growth in sequence data

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