Which alignment tools are supported by this skill?

The skill primarily utilizes MAFFT for multiple sequence alignment, offering various modes ranging from high-speed heuristics for large datasets to high-accuracy local pair alignments for smaller sets.

How does it handle very large datasets?

For datasets with more than 1,000 sequences where traditional maximum likelihood might be too slow, the skill provides an integrated FastTree workflow for approximate ML inference.

Does it include automatic model selection?

Yes, the IQ-TREE 2 implementation automatically performs model selection (ModelFinder) to identify the best-fit substitution model for your specific data.

Can this skill handle both DNA and protein sequences?

Yes, it includes specialized logic and model selection for both nucleotide (DNA) and amino acid (protein/proteomic) sequence data.

What visualization options are available?

The skill uses the ETE3 library to render trees in rectangular or circular modes, color-code taxa by group, and export results to standard image formats like PNG.

Phylogenetics Analysis

Name: Phylogenetics Analysis
Author: henriquescastilho

byhenriquescastilho

•

Ciencia de Datos y ML

Automates the reconstruction and analysis of evolutionary relationships using industry-standard bioinformatics tools like MAFFT and IQ-TREE.

This skill provides a comprehensive pipeline for phylogenetic research, enabling users to perform multiple sequence alignment, tree inference, and visualization within a unified workflow. By integrating tools like MAFFT for alignment, IQ-TREE 2 for maximum likelihood estimation, and ETE3 for tree manipulation, it streamlines complex tasks such as viral phylodynamics, protein family analysis, and molecular clock studies. It is specifically designed for researchers and bioinformaticians who need to infer common ancestry and evolutionary patterns from large-scale genomic or proteomic datasets.

Características Principales

01Fast approximate tree building for large datasets (>1000 sequences) using FastTree.

02Programmatic tree visualization and statistical analysis using the ETE3 Python library.

03Maximum likelihood tree inference with IQ-TREE 2 including automatic model selection.

04Automated alignment trimming via TrimAl to remove noisy columns and improve signal.

05Multiple sequence alignment using MAFFT with auto-selection for speed and accuracy.

061 GitHub stars

Casos de Uso

01Inferring evolutionary relationships and ancestral sequences within protein families.

02Detecting horizontal gene transfer and discordant species-gene trees in microbiology.

03Tracing viral outbreak transmission and estimating divergence dates in phylodynamics.

Características Principales

01Fast approximate tree building for large datasets (>1000 sequences) using FastTree.

02Programmatic tree visualization and statistical analysis using the ETE3 Python library.

03Maximum likelihood tree inference with IQ-TREE 2 including automatic model selection.

04Automated alignment trimming via TrimAl to remove noisy columns and improve signal.

05Multiple sequence alignment using MAFFT with auto-selection for speed and accuracy.

061 GitHub stars

Casos de Uso

01Inferring evolutionary relationships and ancestral sequences within protein families.

02Detecting horizontal gene transfer and discordant species-gene trees in microbiology.

03Tracing viral outbreak transmission and estimating divergence dates in phylodynamics.