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Apollo: a sequencing-technology-independent, scalable and accurate assembly polishing algorithm.

Can Firtina1, Jeremie S Kim1,2, Mohammed Alser1

  • 1Department of Computer Science, ETH Zurich, Zurich 8092, Switzerland.

Bioinformatics (Oxford, England)
|March 14, 2020
PubMed
Summary

Apollo is a new algorithm that fixes errors in genome assemblies using reads from any sequencing technology. It efficiently polishes large genomes without needing to split them, improving genome analysis accuracy.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Third-generation sequencing technologies produce long DNA reads (up to 2 million base pairs) crucial for genome assembly.
  • These long reads have high error rates, leading to inaccuracies in genome assemblies that impact downstream analysis.
  • Current assembly polishing algorithms are limited by technology- or assembly-size dependency, requiring multiple runs or genome fragmentation.

Purpose of the Study:

  • To develop a universal assembly polishing algorithm, Apollo, that overcomes limitations of existing methods.
  • To enable polishing of any-sized genome using reads from all sequencing technologies in a single run.
  • To improve the accuracy and scalability of genome assembly polishing.

Main Methods:

  • Apollo models genome assemblies as profile hidden Markov models (pHMMs).
  • It utilizes read-to-assembly alignment information to train the pHMM using the Forward-Backward algorithm.
  • The trained pHMM is decoded with the Viterbi algorithm to generate a polished assembly.

Main Results:

  • Apollo is a universal algorithm, accommodating reads from any sequencing technology in one execution.
  • It demonstrates excellent scalability for polishing large genome assemblies without requiring fragmentation.
  • Experiments with real-world data confirm Apollo's effectiveness in improving assembly accuracy.

Conclusions:

  • Apollo provides a unified solution for assembly polishing, integrating diverse sequencing data.
  • The algorithm's scalability and technology-agnostic nature significantly advance genome assembly refinement.
  • Apollo offers a more efficient and accurate approach for researchers in genome analysis.