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Bit-reproducible parallel phylogenetic tree inference.

Christoph Stelz1,2, Lukas Hübner1,2, Alexandros Stamatakis3,1,2

  • 1Institute of Theoretical Informatics, Karlsruhe Institute of Technology, Karlsruhe 76131, Germany.

Bioinformatics (Oxford, England)
|January 30, 2026
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Summary
This summary is machine-generated.

Floating-point rounding errors in parallel phylogenetic inference cause significant discrepancies in evolutionary tree results. This study introduces ReproRed, a novel reduction algorithm and the first bit-reproducible tool for accurate phylogenetic analysis.

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Area of Science:

  • Computational Biology
  • Bioinformatics
  • Evolutionary Biology

Background:

  • Phylogenetic trees reconstruct evolutionary history using genomic data.
  • Maximum Likelihood (ML) inference methods are widely used for phylogenetic analysis.
  • Parallel computation in ML inference introduces rounding errors due to floating-point arithmetic, affecting results.

Purpose of the Study:

  • To investigate the impact of parallel computation on the reproducibility of ML phylogenetic inference.
  • To develop a method for achieving bit-reproducible results in parallel phylogenetic analyses.
  • To introduce a general algorithm for reproducible parallel reduction operations.

Main Methods:

  • Developed the ReproRed reduction algorithm to maintain a fixed operation order, independent of parallel execution patterns.
  • Integrated ReproRed into RAxML-NG, a widely used phylogenetic inference tool, to create a bit-reproducible version.
  • Evaluated the performance and reproducibility of the ReproRed algorithm and the enhanced RAxML-NG on empirical datasets.

Main Results:

  • Varying parallelism led to diverging phylogenetic tree searches in over 31% of tested datasets.
  • 8% of diverging datasets yielded statistically significantly worse trees compared to the best known ML tree.
  • The ReproRed-enhanced RAxML-NG achieved bit-reproducible results with minimal performance slowdown (median 0.8%) on up to 768 cores.

Conclusions:

  • Non-reproducibility in parallel phylogenetic inference is a significant issue impacting evolutionary analyses.
  • ReproRed provides a general solution for reproducible associative parallel reduction operations, applicable beyond phylogenetics.
  • The developed bit-reproducible RAxML-NG tool ensures reliable phylogenetic inference across different computational environments.