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Related Experiment Videos

Noisy: identification of problematic columns in multiple sequence alignments.

Andreas W M Dress1, Christoph Flamm, Guido Fritzsch

  • 1Department of Combinatorics and Geometry (DCG), MPG/CAS Partner Institute for Computational Biology (PICB), Shanghai Institutesfor Biological Sciences (SIBS), Shanghai, PR China. andreas@picb.ac.cn

Algorithms for Molecular Biology : AMB
|June 26, 2008
PubMed
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This study introduces a method to identify and remove uninformative homoplastic sites from sequence alignments, improving phylogenetic tree reconstruction. Removing these sites enhances tree stability and accuracy, especially for datasets with low bootstrap support.

Area of Science:

  • Computational Biology
  • Phylogenetics
  • Bioinformatics

Background:

  • Phylogenetic reconstruction from sequence data is challenged by homoplasies and alignment errors, particularly with large evolutionary distances.
  • Variations in substitution rates create a mix of informative and randomized regions within protein-coding genes.
  • Alignment errors in highly variable regions can lead to misleading phylogenetic signals.

Purpose of the Study:

  • To develop a method for identifying phylogenetically uninformative homoplastic sites in multiple sequence alignments.
  • To assess the impact of removing these sites on the performance and quality of phylogenetic reconstruction.
  • To provide a computational tool for implementing this approach.

Main Methods:

  • A novel method is presented that assesses character state distributions along a cyclic ordering of taxa.

Related Experiment Videos

  • This method identifies homoplastic sites that are uninformative for phylogenetic reconstruction.
  • The identified sites are subsequently removed from the sequence alignment.

    • Main Results:

    • Removal of phylogenetically uninformative homoplastic sites demonstrably improves phylogenetic reconstruction performance.
    • Tree quality indices show significant improvement after site exclusion.
    • More stable phylogenetic trees are obtained by excluding incompatible and randomized characters.

    Conclusions:

    • The developed method effectively identifies and removes problematic sites, enhancing phylogenetic accuracy.
    • The 'noisy' software program implements this approach, offering improved phylogenetic reconstruction.
    • This method is particularly beneficial for datasets with low average bootstrap support and at least 12-15 taxa.