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A Rapid Bootstrap Algorithm for the RAxML Web Servers by Alexandros Stamatakis; Paul Hoover; Jacques Rougemont is a Biochemistry, Genetics and Molecular Biology article available to read on EtoBox.

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Despite recent advances achieved by application of high-performance computing methods and novel algorithmic techniques to maximum likelihood (ML)-based inference programs, the major computational bottleneck still consists in the computation of bootstrap support values. Conducting a probably insufficient number of 100 bootstrap (BS) analyses with current ML programs on large datasets-either with respect to the number of taxa or base pairs-can easily require a month of run time. Therefore, we have developed, implemented, and thoroughly tested rapid bootstrap heuristics in RAxML (Randomized Axelerated Maximum Likelihood) that are more than an order of magnitude faster than current algorithms. These new heuristics can contribute to resolving the computational bottleneck and improve current methodology in phylogenetic analyses. Computational experiments to assess the performance and relative accuracy of these heuristics were conducted on 22 diverse DNA and AA (amino acid), single gene as well as multigene, real-world alignments containing 125 up to 7764 sequences. The standard BS (SBS) and rapid BS (RBS) values drawn on the best-scoring ML tree are highly correlated and show almost iden

Who reads A Rapid Bootstrap Algorithm for the RAxML Web Servers?

Author

Alexandros Stamatakis; Paul Hoover; Jacques Rougemont

Publisher

Oxford University Press (OUP)

Published

2008

Language

EN

Field

Biochemistry, Genetics and Molecular Biology (Life Sciences)