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AxPcoords & parallel AxParafit: statistical co-phylogenetic analyses on thousands of taxa

Alexandros Stamatakis12*, Alexander F Auch3, Jan Meier-Kolthoff3 and Markus Göker4

Author Affiliations

1 École Polytechnique Fédérale de Lausanne, School of Computer & Communication Sciences, Laboratory for Computational Biology and Bioinformatics STATION 14, CH-1015 Lausanne, Switzerland

2 Swiss Institute of Bioinformatics

3 Center for Bioinformatics (ZBIT), Sand 14, Tübingen, University of Tübingen, Germany

4 Organismic Botany/Mycology, Auf der Morgenstelle 1, Tübingen, University of Tübingen, Germany

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BMC Bioinformatics 2007, 8:405  doi:10.1186/1471-2105-8-405

Published: 22 October 2007

Abstract

Background

Current tools for Co-phylogenetic analyses are not able to cope with the continuous accumulation of phylogenetic data. The sophisticated statistical test for host-parasite co-phylogenetic analyses implemented in Parafit does not allow it to handle large datasets in reasonable times. The Parafit and DistPCoA programs are the by far most compute-intensive components of the Parafit analysis pipeline. We present AxParafit and AxPcoords (Ax stands for Accelerated) which are highly optimized versions of Parafit and DistPCoA respectively.

Results

Both programs have been entirely re-written in C. Via optimization of the algorithm and the C code as well as integration of highly tuned BLAS and LAPACK methods AxParafit runs 5–61 times faster than Parafit with a lower memory footprint (up to 35% reduction) while the performance benefit increases with growing dataset size. The MPI-based parallel implementation of AxParafit shows good scalability on up to 128 processors, even on medium-sized datasets. The parallel analysis with AxParafit on 128 CPUs for a medium-sized dataset with an 512 by 512 association matrix is more than 1,200/128 times faster per processor than the sequential Parafit run. AxPcoords is 8–26 times faster than DistPCoA and numerically stable on large datasets. We outline the substantial benefits of using parallel AxParafit by example of a large-scale empirical study on smut fungi and their host plants. To the best of our knowledge, this study represents the largest co-phylogenetic analysis to date.

Conclusion

The highly efficient AxPcoords and AxParafit programs allow for large-scale co-phylogenetic analyses on several thousands of taxa for the first time. In addition, AxParafit and AxPcoords have been integrated into the easy-to-use CopyCat tool.