SeqVis: Visualization of compositional heterogeneity in large alignments of nucleotides | Zendy

Joshua W. K. Ho | Zendy; Cameron E. Adams | Zendy; JieBin Lew | Zendy; Timothy James Matthews | Zendy; Chiu Chin Ng | Zendy; Arash Shahabi-Sirjani | Zendy; Leng Hong Tan | Zendy; Yu Zhao | Zendy; Simon Easteal | Zendy; Susan R. Wilson | Zendy; Lars S. Jermiin | Zendy

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SeqVis: Visualization of compositional heterogeneity in large alignments of nucleotides

Author(s) -

Joshua W. K. Ho,

Cameron E. Adams,

JieBin Lew,

Timothy James Matthews,

Chiu Chin Ng,

Arash Shahabi-Sirjani,

Leng Hong Tan,

Yu Zhao,

Simon Easteal,

Susan R. Wilson,

Lars S. Jermiin

Publication year - 2006

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btl283

Subject(s) - phylogenetic tree , outlier , visualization , computer science , homogeneous , java , phylogenetics , sequence (biology) , computational biology , data mining , biology , genetics , mathematics , artificial intelligence , programming language , combinatorics , gene

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.

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