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SeqVis: a tool for detecting compositional heterogeneity among aligned nucleotide sequences.

Lars Sommer Jermiin1, Joshua Wing Kei Ho, Kwok Wai Lau

  • 1School of Biological Sciences, Centre for Mathematical Biology and Sydney Bioinformatics, University of Sydney, Sydney, Australia.

Methods in Molecular Biology (Clifton, N.J.)
|April 21, 2009
PubMed
Summary
This summary is machine-generated.

Compositional heterogeneity in nucleotide and amino acid sequences is common, challenging standard phylogenetic methods. SeqVis offers a tool to detect these evolutionary variations in aligned nucleotide sequences.

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Published on: February 5, 2014

Area of Science:

  • Molecular Evolution
  • Bioinformatics
  • Phylogenetics

Background:

  • Compositional heterogeneity is an underappreciated characteristic of aligned nucleotide and amino acid sequences.
  • This heterogeneity, observed across sequences or sites, contradicts assumptions of homogeneous evolutionary conditions in standard phylogenetic analyses.
  • Violated phylogenetic assumptions can lead to inaccurate evolutionary inferences.

Purpose of the Study:

  • To introduce and evaluate SeqVis, a program designed for surveying compositional heterogeneity in aligned nucleotide sequences.
  • To discuss the advantages and limitations of SeqVis compared to existing methods for detecting phylogenetic assumption violations.
  • To demonstrate the utility of SeqVis in analyzing real-world nucleotide sequence data.

Main Methods:

  • SeqVis program for surveying aligned nucleotide sequences.
  • Comparative analysis of SeqVis against other methods for detecting compositional heterogeneity.
  • Application of SeqVis to two nucleotide alignment datasets, including one with 7542 nucleotides from 53 species.

Main Results:

  • SeqVis effectively surveys compositional heterogeneity in nucleotide sequence alignments.
  • The study highlights the pros and cons of SeqVis in the context of phylogenetic assumption testing.
  • Demonstrated benefits of SeqVis in analyzing substantial nucleotide datasets.

Conclusions:

  • Compositional heterogeneity is a significant factor in molecular evolution that requires robust detection methods.
  • SeqVis provides a valuable tool for identifying deviations from homogeneous evolutionary models in nucleotide sequences.
  • Accurate phylogenetic reconstruction necessitates accounting for the complex evolutionary conditions revealed by compositional heterogeneity.