egt — Evolutionary Genome Topology

egt is a Python / Snakemake analysis toolkit for characterizing chromosome evolution across metazoan genomes. It builds on reciprocal-best-hits data from odp and provides tools for:

• ALG (ancestral linkage group) fusion, dispersal, and rate analyses
• PhyloTreeUMAP: manifold projection of per-species ALG state (MGT, MLT, and one-dot-one-genome variants)
• perspective-chromosome reconstruction with Monte Carlo support
• branch-wise rate analyses against a calibrated tree
• Fourier-period analysis of rate time series
• phylogenetic subsampling, tree prep, taxonomy utilities

Getting Started

git clone https://github.com/conchoecia/egt.git
cd egt
python -m venv .venv && source .venv/bin/activate
pip install -e .

egt --help
bash tests/smoke/test_cli.sh

Primary input is a directory of per-species RBH files produced by odp against the BCnS ALG database. From there, most analyses are a single egt <subcommand> call or a Snakefile under workflows/.

Quick Start

PhyloTreeUMAP — manifold projection of per-species ALG state

# 1. build per-sample distance matrices + sampledf
egt phylotreeumap build-distances \
    --rbh-dir /path/to/rbh_files \
    --alg-name BCnSSimakov2022 \
    --sampledf-out GTUMAP/sampledf.tsv \
    --distance-dir GTUMAP/distance_matrices/

# 2. index ALG locus pairs
egt phylotreeumap algcomboix \
    --alg-rbh /path/to/LG_db/BCnSSimakov2022/BCnSSimakov2022.rbh \
    --output GTUMAP/alg_combo_to_ix.tsv

# 3. run the UMAP + HTML plot (MGT / MLT / ODOG variants)
egt phylotreeumap mgt-mlt-umap --help

ALG fusion analysis on a calibrated tree

egt alg-fusions --help

Perspective-chromosome tree mapping + Monte Carlo rates

egt perspchrom-df-to-tree --help

Rate analyses, Fourier periodicity, branch stats

egt branch-stats-vs-time    --help
egt fourier-of-rates        --help
egt fourier-support-vs-time --help
egt collapsed-tree          --help
egt tree-changes            --help
egt decay-pairwise          --help
egt decay-many-species      --help

Phylogeny preparation

egt taxids-to-newick           --help
egt newick-to-common-ancestors --help

Users' Guide

egt is a collection of analysis scripts rather than a monolithic pipeline. Each script is also registered as a subcommand of the egt console script:

egt alg-fusions --help
# equivalent to
python -m egt.plot_alg_fusions --help

Installation

git clone https://github.com/conchoecia/egt.git
cd egt
python -m venv .venv && source .venv/bin/activate
pip install -e .

Python requirements

Python 3.10 or newer. pip install -e . pulls the deps from pyproject.toml:

• numpy, pandas, scipy, scikit-learn, matplotlib, networkx, Pillow
• umap-learn[plot] — UMAP + the plotting extras needed by PhyloTreeUMAP
• bokeh — interactive HTML plots
• ete4 — taxonomy trees and NCBI taxid handling
• snakemake (>=7, <9)
• pyyaml

Conda equivalent:

mamba install -c conda-forge -c bioconda \
      python=3.11 numpy pandas scipy scikit-learn matplotlib networkx pillow \
      "umap-learn" bokeh ete4 "snakemake<9" pyyaml
pip install --no-deps -e .

Upstream tools

egt consumes outputs of several companion tools:

• odp — per-species RBH files, ALG databases (BCnSSimakov2022 etc.)
• chrombase — chromosome-scale NCBI genome database builder
• genbargo — embargo-aware assembly curation
• chromsim — chromosome-evolution simulations

CLI overview

phylotreeumap             — UMAP-over-ALG-topology (MGT, MLT, ODOG subcommands)
phylotreeumap-subsample   — subsample species phylogenetically with per-clade caps
alg-fusions               — plot fusion events on a phylogeny (canonical v3)
alg-dispersion            — plot ALG dispersion across species
perspchrom-df-to-tree     — map perspective-chromosome changes onto a tree (Monte Carlo)
decay-pairwise            — pairwise ALG-decay analysis
decay-many-species        — cross-species ALG conservation / decay
chrom-number-vs-changes   — chromosome count vs rearrangement-rate scatter
branch-stats-vs-time      — branch statistics against geologic time
branch-stats-tree         — branch statistics laid out on a tree
branch-stats-tree-pair    — paired branch-stats tree plots
collapsed-tree            — collapsed-tree visualization
tree-changes              — per-branch changes on a tree
fourier-of-rates          — Fourier analysis of chromosomal change rates
fourier-support-vs-time   — Fourier-support-vs-time plots
count-unique-changes      — count unique changes per branch
defining-features         — identify clade-defining features
defining-features-plot    — plot defining features
defining-features-plotRBH — plot defining features on RBH dataframes
taxids-to-newick          — build a Newick tree from NCBI taxids
newick-to-common-ancestors — divergence-time annotation from a timetree
algs-split-across-scaffolds — find ALGs split across scaffolds
get-assembly-sizes        — summarize assembly sizes
pull-entries-from-yaml    — select rows from a YAML sample list
aggregate-filechecker     — aggregate filechecker benchmarks
aggregate-filesizes       — aggregate file-size summaries
join-supplementary-tables — join table fragments
phylotreeumap-plotdfs     — PhyloTreeUMAP plotting dataframe helper

Snakemake workflows

Multi-stage Snakemake definitions live under workflows/:

workflows/
├── phylotree_umap.smk
├── phylotree_umap_subsampling.smk
├── perspchrom_df_stats_and_mc.smk
├── annotate_sample_df.smk
├── sample_to_num_chromosomes.smk
├── odol_annotate_blast.smk
└── pipeline/
    ├── README.md
    ├── config.template.yaml
    └── run.sh

Each workflow is standalone and parameterized via a YAML config.

Input file formats

• RBH files (.rbh) — tab-separated reciprocal-best-hits output of odp. Filenames must embed the NCBI taxid as the second hyphen-separated field, e.g. speciesname-7777-something.rbh.
• Sample dataframe (sampledf.tsv) — output of egt phylotreeumap build-distances; consumed by most downstream commands.
• ALG database RBH — e.g. BCnSSimakov2022.rbh, from odp's LG_db.
• Newick trees — ete4-readable. egt taxids-to-newick emits these.
• Divergence-time tables — TSV, as accepted by egt newick-to-common-ancestors.

Layout

egt/
├── src/egt/                    — Python package
│   ├── cli.py                  — argparse dispatcher
│   ├── _vendor/                — vendored, frozen plotting utilities
│   ├── legacy/                 — prior versions of plot_ALG_fusions kept for parity
│   └── *.py                    — one module per subcommand
├── workflows/                  — Snakemake workflows
├── configs/                    — example configs
├── data/                       — small bundled data
├── tests/
│   ├── testdb/                 — mini_hydra + mini_urchin fixtures
│   └── smoke/test_cli.sh       — CLI smoke test
└── docs/

Related tools

• odp
• chrombase
• genbargo
• chromsim

Citing egt

If you use this toolkit, please cite:

Schultz, D.T., Blümel, A., Destanović, D., Sarigol, F., Simakov, O. (2024). Topological mixing and irreversibility in animal chromosome evolution. bioRxiv. doi:10.1101/2024.07.29.605683

For background on the topological framework for comparative genomics, see:

Schultz, D.T., Simakov, O. (2026). Topological Approaches in Animal Comparative Genomics. Annual Review of Animal Biosciences 14(1), 17–48. doi:10.1146/annurev-animal-030424-084541

See also CITATION.cff.

License

MIT — see LICENSE.