ebolaseq

EbolaSeq

EbolaSeq is a command-line tool that simplifies the process of analyzing Ebola virus sequences. It automates the complete workflow from downloading sequences to creating phylogenetic trees. The tool retrieves Ebola virus sequences from NCBI GenBank, processes them according to user specifications, performs multiple sequence alignment and generates phylogenetic trees.

Installation

Prerequisites

First, install conda if you haven’t already:

wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
bash Miniconda3-latest-Linux-x86_64.sh

Then, ensure you have the required channels:

conda config --add channels defaults
conda config --add channels bioconda
conda config --add channels conda-forge

Option 1: Using Conda (Recommended)

Install EbolaSeq via Conda:

conda create -n ebolaseq -c conda-forge -c bioconda ebolaseq -y
conda activate ebolaseq

Option 2: From source

conda create -n ebolaseq -c conda-forge -c bioconda python=3.9 mafft trimal iqtree=2.4.0 biopython minimap2 pal2nal
conda activate ebolaseq
git clone https://github.com/DaanJansen94/ebolaseq.git
cd ebolaseq
pip install .

Usage

conda activate ebolaseq
ebolaseq -o OUTPUT_DIR [options] 

EbolaSeq can be run in two modes:

1. Interactive Mode (default) - for interactive use
2. Non-Interactive Mode - for HPC submissions or automated runs

Options

-o, --output-dir — Output directory for results

--virus — Virus / species

• 1 = Zaire ebolavirus
• 2 = Sudan ebolavirus
• 3 = Bundibugyo ebolavirus
• 4 = Tai Forest ebolavirus
• 5 = Reston ebolavirus
• 6 = Pan-Ebola: all 5 species
• Comma-separated = multiple species (e.g. 1,2 for Zaire+Sudan; 1,2,3 for Zaire+Sudan+Bundibugyo)

--genome — Genome completeness

• 1 = Complete genomes only
• 2 = Partial genomes (requires --completeness)
• 3 = All genomes

--completeness — Required when --genome=2

• Value between 1–100 (percentage)

--host — Host filter

• 1 = Human only
• 2 = Non-human only
• 3 = All hosts

--metadata — Metadata filter

• 1 = Location only
• 2 = Date only
• 3 = Both location and date
• 4 = None

Optional

--beast — Required when --metadata is 2 or 3

• 1 = No
• 2 = Yes

Consensus FASTA per species — Path to a FASTA file

• --c_z = Zaire
• --c_s = Sudan
• --c_r = Reston
• --c_b = Bundibugyo
• --c_t = Tai Forest

--alignment, -a — Alignment type

• 1 = Whole-genome alignment
• 2 = Protein (CDS) alignment
• 3 = No alignment

--proteins, -pr — For alignment 2 only; comma-separated

• 1 = L (RNA-dependent RNA polymerase)
• 2 = NP (nucleoprotein)
• 3 = VP35 (polymerase cofactor)
• 4 = VP40 (matrix protein)
• 5 = GP (spike glycoprotein)
• 6 = VP30 (minor nucleoprotein)
• 7 = VP24 (membrane-associated protein)
• Or use names: L, NP, VP35, VP40, GP, VP30, VP24

--phylogeny, -p — Create phylogenetic tree from alignment

-m, --min-cds-fraction — For alignment 2: minimum fraction of reference CDS length to keep a sequence (default 0.5). E.g. 0.2 keeps more partial sequences, 0.8 is stricter.

-t, --threads — Threads for minimap2 and MAFFT (default 1). E.g. -t 64 on a 64-core node. 0 = use all CPUs.

--remove — Path to file listing sequence IDs/headers to exclude

Examples

# Interactive (prompts for all choices)
ebolaseq -o my_analysis

# Non-interactive: Zaire, complete genomes, human, location+date, whole-genome alignment + phylogeny
ebolaseq -o my_analysis --virus 1 --genome 1 --host 1 --metadata 3 --alignment 1 --phylogeny

# Pan-Ebola, protein alignment (L and NP), phylogeny per protein, consensus for Zaire and Sudan
ebolaseq -o my_analysis --virus 6 --genome 1 --host 3 --metadata 4 \
  --c_z consensus_zaire.fasta --c_s consensus_sudan.fasta \
  --alignment 2 -pr L,NP --phylogeny

# Exclude specific sequences
ebolaseq -o my_analysis --virus 1 --genome 1 --host 1 --metadata 4 --remove exclude.txt

Output

• FASTA/ — Filtered sequences and location.txt.
• Alignment/ — For whole-genome: FASTA/, MAFFT/, Trimmed/. For protein: pan/ (or species name) with e.g. L/, NP/ each containing cds_aligned.fasta.
• Phylogeny/ — IQTree2 results (whole-genome: one tree; protein: one folder per protein).
• summary_*.txt — Run summary and location counts.

Notes

• Use --remove with a list of IDs to exclude cell-culture, lab-adapted, or other non-natural sequences.
• For large Zaire trees, consider rooting with 1976 Yambuku outbreak sequences.

Dependencies

• Python ≥ 3.9
• Biopython ≥ 1.81
• MAFFT, TrimAl, IQTree2
• For protein alignment: minimap2, pal2nal

Citation

If you use EbolaSeq in your research, please cite:

Jansen, D., & Vercauteren, K. (2025). EbolaSeq: A Command-Line Tool for Downloading, Processing, and Analyzing Ebola Virus Sequences for Phylogenetic Analysis (v0.1.8). Zenodo. https://doi.org/10.5281/zenodo.14851686

License

This project is licensed under the GNU General Public License v3.0 (GPL-3.0) - see the LICENSE file for details.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

Support

If you encounter any problems or have questions, please open an issue on GitHub.

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