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SeqVis: Visualization of compositional heterogeneity in large alignments of nucleotides

  • Joshua W.K. Ho
  • , Cameron E. Adams
  • , Jie Bin Lew
  • , Timothy J. Matthews
  • , Chiu Chin Ng
  • , Arash Shahabi-Sirjani
  • , Leng Hong Tan
  • , Yu Zhao
  • , Simon Easteal
  • , Susan R. Wilson
  • , Lars S. Jermiin
  • School of Biological Sciences
  • Sydney University Biological Informatics and Technology Centre (SUBIT)

Research output: Contribution to a Journal (Peer & Non Peer)Articlepeer-review

47 Citations (Scopus)

Abstract

Summary: Most phylogenetic methods assume that the sequences evolved under homogeneous, stationary and reversible conditions. Compositional heterogeneity in data intended for studies of phylogeny suggests that the data did not evolve under these conditions. SeqVis, a Java application for analysis of nucleotide content, reads sequence alignments in several formats and plots the nucleotide content in a tetrahedron. Once plotted, outliers can be identified, thus allowing for decisions on the applicability of the data for phylogenetic analysis.

Original languageEnglish
Pages (from-to)2162-2163
Number of pages2
JournalBioinformatics
Volume22
Issue number17
DOIs
Publication statusPublished - 1 Sep 2006
Externally publishedYes

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