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Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

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Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
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Published on: August 14, 2018

Accurate extension of multiple sequence alignments using a phylogeny-aware graph algorithm.

Ari Löytynoja1, Albert J Vilella, Nick Goldman

  • 1EMBL-European Bioinformatics Institute, Hinxton, CB10 1SD, UK. ari.loytynoja@helsinki.fi

Bioinformatics (Oxford, England)
|April 26, 2012
PubMed
Summary
This summary is machine-generated.

PAGAN enhances sequence alignment by incorporating phylogenetic information, improving accuracy for fragmented and noisy data. This method accurately extends existing alignments without full recomputation, aiding evolutionary analyses.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Evolutionary Biology

Background:

  • Accurate sequence alignment is computationally intensive, especially with large datasets.
  • Extending existing alignments with new or fragmented sequences is challenging.
  • Current methods often lack phylogenetic awareness and are sensitive to reference set composition.

Purpose of the Study:

  • To develop a novel method for phylogeny-aware alignment extension.
  • To improve the accuracy and efficiency of adding new sequences to existing alignments.
  • To address challenges posed by fragmented sequences from sources like next-generation metagenomics.

Main Methods:

  • Developed PAGAN, a method for phylogeny-aware alignment of partial-order sequence graphs.
  • Inferred ancestral sequences for reference alignments.
  • Integrated new sequences into their phylogenetic context within existing alignments.
  • Applied the method to extend alignments with new and fragmented sequence data.

Main Results:

  • PAGAN accurately extends alignments by considering phylogenetic relatedness.
  • Outperforms alternative methods in alignment extension accuracy for both DNA and protein data.
  • Shows significant improvement for fragmented sequences and noisy next-generation sequencing (NGS) data.
  • Generated alignments are suitable for evolutionary analyses, including RNA-seq data.

Conclusions:

  • PAGAN offers a superior approach to alignment extension by leveraging phylogenetic information.
  • The method is robust to the inclusion of divergent sequences and handles fragmented data effectively.
  • PAGAN facilitates more accurate evolutionary analyses with large and complex sequence datasets.