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Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
Published on: August 14, 2018
Phylometrics: a pipeline for inferring phylogenetic trees from a sequence relationship network perspective
Samuel A Smits1, Cleber C Ouverney
1Department of Biological Sciences, San José State University, One Washington Square, San José, California 95192-0100, USA. samsmits@gmail.com
BMC Bioinformatics
|October 16, 2010
Summary
Phylometrics analyzes microbial diversity by examining sequence relationship networks, not just top BLASTN hits. This automated tool identifies phylogenetically significant DNA sequences for better evolutionary insights.
Area of Science:
- Microbiology
- Bioinformatics
- Computational Biology
Background:
- 16S rRNA gene sequence analysis is standard for microbial diversity but can misrepresent relatedness due to evolutionary factors.
- Relying solely on top BLASTN hits may distort phylogenetic studies, while including numerous hits complicates analysis.
- Sequence relationship networks offer a more accurate method to identify closely related sequences, even with low BLASTN ranks.
Purpose of the Study:
- To develop an automated, high-throughput web application for phylogenetic tree construction.
- To provide novel tools for identifying phylogenetically significant sequences with minimal user intervention.
- To offer a user-friendly platform for analyzing microbial diversity and evolutionary relationships.
Main Methods:
- Developed Phylometrics, a web application utilizing networks of collective BLASTN results.
- Implemented a wizard-style interface for guided pipeline execution without programming knowledge.
- Integrated an independent job queuing system for efficient, high-throughput processing.
Main Results:
- Phylometrics automates phylogenetic tree building using sequence relationship networks.
- The application effectively identifies sequences of significant phylogenetic interest.
- It allows users to continue system use during job execution with minimal performance impact.
Conclusions:
- Phylometrics offers a novel data mining approach for screening DNA sequences.
- Identifies sequences with potential functional or evolutionary relatedness through network analysis.
- Requires only basic computer skills, similar to internet navigation.
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