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Updated: Dec 19, 2025

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Published on: August 14, 2018

PIQMEE: Bayesian Phylodynamic Method for Analysis of Large Data Sets with Duplicate Sequences.

Veronika Boskova^1,2,3, Tanja Stadler^1,2

¹Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland.

Molecular Biology and Evolution

|June 4, 2020

Summary

This summary is machine-generated.

Analyzing large pathogen sequencing datasets computationally is challenging. We developed PIQMEE, a new tool for accurate and efficient phylogenetic and phylodynamic analysis of complex sequence data, improving computational efficiency for large datasets.

Keywords:

BEAST 2 Bayesian phylodynamics duplicate sequences fast algorithms large data sets subsampling

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Last Updated: Dec 19, 2025

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Published on: August 16, 2017

Area of Science:

Computational Biology
Bioinformatics
Evolutionary Genetics

Background:

Next-generation sequencing generates vast pathogen quasispecies data, often with numerous identical sequences.
Large datasets pose computational challenges for existing Bayesian phylogenetic and phylodynamic methods.

Purpose of the Study:

To evaluate the impact of duplicate sequences on phylogenetic and phylodynamic analysis speed and accuracy.
To introduce PIQMEE, a novel BEAST 2 add-on for efficient analysis of large sequence datasets.

Main Methods:

Simulations were used to test the effects of unique, random subsets, and full datasets on phylogenetic analysis.
PIQMEE was developed to resolve unique sequence tree structures while estimating duplicate sequence divergence times.
Computational efficiency and accuracy were compared against existing BEAST 2 methods.

Main Results:

Using only unique sequences introduces bias; random subsets lead to imprecise estimates.
PIQMEE significantly enhances computational efficiency, converging in approximately 1 day for 6,000 sequences, compared to 7 days for classic methods.
PIQMEE successfully handles datasets up to 21,000 sequences, demonstrating scalability.

Conclusions:

PIQMEE offers a reliable and computationally efficient solution for analyzing large pathogen quasispecies datasets.
The method accurately estimates phylogenetic and phylodynamic parameters from full datasets, overcoming limitations of current approaches.
PIQMEE was successfully applied to within-host HIV sequencing data, showcasing its real-world applicability.