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W-IQ-TREE: a fast online phylogenetic tool for maximum likelihood analysis.
Jana Trifinopoulos1, Lam-Tung Nguyen1, Arndt von Haeseler2
1Center for Integrative Bioinformatics, Max F. Perutz Laboratories, University of Vienna, Medical University of Vienna, 1030 Vienna, Austria.
Nucleic Acids Research
|April 17, 2016
Summary
W-IQ-TREE provides a user-friendly web interface for IQ-TREE, enabling efficient phylogenetic analysis with diverse data types and evolutionary models. This tool simplifies complex maximum likelihood phylogenetic tree reconstruction and testing for researchers.
Area of Science:
- Computational Biology
- Evolutionary Biology
- Bioinformatics
Background:
- Phylogenetic analysis is crucial for understanding evolutionary relationships.
- IQ-TREE is an efficient software for phylogenetic analysis using maximum likelihood methods.
- A user-friendly interface can enhance accessibility to advanced phylogenetic tools.
Purpose of the Study:
- To present W-IQ-TREE, a web interface and server for IQ-TREE.
- To provide an intuitive platform for maximum likelihood phylogenetic analysis.
- To support diverse sequence types and evolutionary models.
Main Methods:
- Development of a web interface and server for IQ-TREE.
- Support for multiple sequence types (DNA, protein, codon, binary, morphology).
- Implementation of various evolutionary models, including mixture and partition models.
- Integration of model selection, partition finding, tree reconstruction, bootstrapping, and tree topology testing.
Main Results:
- W-IQ-TREE offers a user-friendly platform for IQ-TREE.
- Supports a wide range of sequence types and evolutionary models.
- Performs fast model selection, partition finding, tree reconstruction, and various statistical tests.
- Computations are performed on a dedicated cluster, with results delivered via URL or email.
Conclusions:
- W-IQ-TREE enhances the accessibility and usability of IQ-TREE for phylogenetic analysis.
- It facilitates efficient and comprehensive phylogenetic inference and testing.
- The platform is freely available and requires no login, making it accessible to all researchers.
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