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Fast tumor phylogeny regression via tree-structured dual dynamic programming.

Henri Schmidt1, Yuanyuan Qi2, Benjamin J Raphael1

  • 1Department of Computer Science, Princeton University, Princeton, NJ 08542, United States.

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Summary
This summary is machine-generated.

This study introduces fastppm, a new computational tool for tumor evolution reconstruction. fastppm significantly speeds up phylogenetic analysis, improving accuracy for bulk DNA sequencing data.

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Area of Science:

  • Computational Biology
  • Genomics
  • Evolutionary Biology

Background:

  • Reconstructing tumor evolutionary history from bulk DNA sequencing is computationally challenging.
  • Phylogenetic reconstruction methods face bottlenecks in solving the regression problem.
  • Existing methods lack fast, specialized algorithms for the perfect phylogeny regression problem.

Purpose of the Study:

  • To introduce fastppm, a novel computational tool for efficient perfect phylogeny regression.
  • To address the computational bottleneck in tumor phylogenetic reconstruction.
  • To enable accurate analysis of low-coverage bulk DNA sequencing data.

Main Methods:

  • Developed fastppm using tree-structured dual dynamic programming.
  • Implemented fastppm in C++ with command-line and Python interfaces.
  • Supported arbitrary, separable convex loss functions, including L2, piecewise linear, binomial, and beta-binomial.

Main Results:

  • fastppm achieves 50-450x speedups over existing regression algorithms with comparable accuracy.
  • Integration of fastppm into phylogeny inference tools resulted in up to 400x speedups.
  • fastppm demonstrated superior accuracy and runtime performance on simulated and real-world colorectal cancer data.

Conclusions:

  • fastppm is a highly efficient and accurate tool for solving the perfect phylogeny regression problem.
  • The tool significantly accelerates tumor phylogenetic reconstruction, enabling analysis of challenging datasets.
  • fastppm improves the accuracy and speed of evolutionary history inference from bulk DNA sequencing.