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Multiple sequence alignment analysis with Affinity Tree generation

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This repository contains tool for multiple sequence alignment analysis. It implements the idea of pan-genome (Ref. 1) by representing the multialignment as a PO-MSA structure (Partial Order Alignment Graph - Ref. 2). The main purpose of this software is to construct an Affinity Tree - a phylogenetic-like tree, with an agreed sequence (consensus sequence) assigned for each node. The result is saved in JSON file (see its schema in pangtree/pangtreebuild/serialization/affinity_tree_schema.json). Its content can be visualised using PangtreeVis.

This software is a part of the article: P.Dziadkiewicz, N.Dojer 'Getting insight into the pan-genome structure with Pangtree' that will be published soon in BMC Genomics.

Getting Started





pip install pangtreebuild

Quick installation check

This line builds a pan-genome model for an example alignment of 160 Ebola virus sequences and saves it to a JSON file.

python3 -m pangtreebuild --multialignment example_data/Ebola/multialignment.maf


  1. Import package pangtreebuild to your Python program and use it according to the documentation.


  1. Use pangtreebuild via command line with following arguments:

python3 -m pangtreebuild [args]

Name CLI Required Description
Arguments affecting PO-MSA construction:
MULTIALIGNMENT --multialignment Yes Path to the mulitalignment file (.maf or .po)
METADATA --metadata No Optional information about sequences in csv format. The only required column: 'seqid' and its value must match multialignment files identifiers as described in Sequence Naming Convention (below). Example: example_data/Ebola/metadata.csv
RAW_MAF --raw_maf No, default=False Build PO-MSA without transforming multialignment (MAF file) to DAG. PO-MSA built in this way does not reflect real life sequences.
FASTA_PROVIDER --fasta_provider No Nucleotides source if any residues are missed in the multialignment file. Possible values: 'ncbi', 'file'. If not specified: MISSING_NUCLEOTIDE is used.
MISSING_SYMBOL --missing_symbol No, default='?' Symbol for missing nucleotides used if no FASTA_PROVIDER is given.
CACHE --cache No If set, sequences downloaded from NCBI are stored on local disc and reused between program calls, used if FASTA_PROVIDER is 'ncbi'
FASTA_PATH -fasta_path Yes if FASTA_PROVIDER='FILE' Path to fasta file or zipped fasta files with whole sequences present in multialignment, used if FASTA_PROVIDER is 'FILE'.
Arguments affecting Affinity Tree construction:
AFFINITY -affinity No Possible values: 'TREE' (default algorithm, descibed in, 'POA' (simplified version, based solely on Ref. 2)
BLOSUM --blosum No, default=bin\blosum80.mat Path to the blosum filem. Blosum file must include MISSING_NUCLEOTIDE.
HBMIN --hbmin No, default=0.9 'POA' parameter. The minimum value of sequence compatibility to generated consensus.
STOP --stop No, default=0.99 'TREE' parameter. Minimum value of compatibility in tree leaves.
P -p No, default=1 'TREE' parameter. It changes the linear meaning of compatiblities during cutoff finding because the compatibilities are raised to the power o P. For P from range [0,1] it decreases distances between small compatibilities and increases distances between the bigger ones. For p > 1 it increases distances between small compatibilities and decreases distances between the bigger ones.
Arguments affecting output generation:
OUTPUT_DIR --output_dir, -o No, default=timestamped folder in current working directory Output directory path.
OUTPUT_FULL --output_full No, default=False Set, if list of pangenome nodes for sequences and consensuses should be included in pangenome.json.
VERBOSE --verbose, -v No, default=False Set if detailed log files must be produced.
QUIET --quiet, -q No, default=False Set to turn off console logging.
FASTA --output_fasta No, default=False Set to create fasta files with consensuses.
PO -output_po No, default=False Set to create po file with multialignment (without consensuses).

Sequence Naming Convention

[seqid].[anything after first dot is ignored]

Example use cases

  1. Build PO-MSA using default settings (transform to DAG, download missing nucleotides from NCBI) and save to .po file :
python -m pangtreebuild --multialignment example_data/Ebola/multialignment.maf -po

will produce:

  • pangenome.json
  • poagraph.po
  1. Generate Affinity Tree, use metadata, detailed logging and default algorithm settings.
python3 -m pangtreebuild --multialignemnt example_data/Ebola/multialignment.maf -metadata example_data/Ebola/metadata.csv -affinity tree -v

will produce:

  • pangenome.json
  • details.log
  • affinitytree/
    • tresholds.csv
    • .po files from internal calls to poa software


python3 -m unittest discover -s pangtreebuild -p tests_*


nosetests pangtreebuild


This software is developed with support of OPUS 11 scientific project of National Science Centre: Incorporating genomic variation information into DNA sequencing data analysis


This project is licensed under the MIT License - see the file for details


  1. Computational pan-genomics: status, promises and challenges The Computational Pan-Genomics Consortium. Briefings in Bioinformatics, Volume 19, Issue 1, January 2018, Pages 118–135.

  2. Generating consensus sequences from partial order multiple sequence alignment graphs C. Lee, Bioinformatics, Volume 19, Issue 8, 22 May 2003, Pages 999–1008

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