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Evolutionary Relationships through Genome Comparisons

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Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...

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Updated: Jul 5, 2025

A Practical Guide to Phylogenetics for Nonexperts

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

Create, Analyze, and Visualize Phylogenomic Datasets Using PhyloFisher.

Robert E Jones^1,2, Alexander K Tice^1,2,3, Marek Eliáš⁴

¹Department of Biological Sciences, Mississippi State University, Starkville, Mississippi, USA.

Current Protocols

|January 24, 2024

Summary

This summary is machine-generated.

PhyloFisher is a new Python3 software package for creating, analyzing, and visualizing eukaryotic phylogenomic datasets. It offers a curated gene database and utilities for robust evolutionary analyses, simplifying complex bioinformatics workflows.

Keywords:

evolution genomics systematics transcriptomics

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Last Updated: Jul 5, 2025

A Practical Guide to Phylogenetics for Nonexperts

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An Integrated Approach for Microprotein Identification and Sequence Analysis

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Published on: July 12, 2022

Area of Science:

Bioinformatics
Computational Biology
Evolutionary Biology

Background:

Phylogenomic datasets are crucial for understanding evolutionary relationships in eukaryotes.
Existing phylogenomic pipelines often lack comprehensive, curated resources and integrated analytical tools.
Efficient construction and analysis of large-scale phylogenomic data remain a challenge.

Purpose of the Study:

To introduce PhyloFisher, a versatile Python3 software package for eukaryotic phylogenomics.
To provide a manually curated database and utilities for streamlined phylogenomic dataset creation and analysis.
To facilitate robust evolutionary studies by addressing common data quality and analytical challenges.

Main Methods:

Development of PhyloFisher, a Python3-based software package.
Inclusion of a manually curated database of 240 eukaryotic protein-coding genes.
Implementation of utilities for data curation, quality control, and supermatrix construction.

Main Results:

PhyloFisher enables the creation, analysis, and visualization of eukaryotic phylogenomic datasets.
The software supports both a curated database and user-defined protein databases.
Integrated utilities facilitate gene/taxa removal, heterogeneity testing, and site/taxa filtering.

Conclusions:

PhyloFisher offers a comprehensive solution for eukaryotic phylogenomic analyses.
The package enhances the efficiency and reliability of constructing and analyzing phylogenomic datasets.
It serves as a valuable tool for researchers investigating eukaryotic evolution.