pangraph

a bioinformatic toolkit to align large sets of closely related genomes into a graph data structure

Overview

pangraph provides both a command line interface, as well as a Julia library, to find homology amongst large collections of closely related genomes. The core of the algorithm partitions each genome into pancontigs that represent a sequence interval related by vertical descent. Each genome is then an ordered walk along pancontigs; the collection of all genomes form a graph that captures all observed structural diversity. pangraph is a standalone tool useful to parsimoniously infer horizontal gene transfer events within a community; perform comparative studies of genome gain, loss, and rearrangement dynamics; or simply to compress many related genomes.

Installation

The core algorithm and command line tools are self-contained and require no additional dependencies. The library is written in and thus requires Julia to be installed on your machine.

pangraph is available:

• as a julia library
• as a Docker container
• it can be compiled into a relocatable binary

For more extended instructions on installation please refer to the documentation.

Note: pangraph was written in Julia version 1.7.2. Compatibility more recent versions of Julia is not guaranteed.

Julia Library

To install pangraph as a julia library in a local environment:

    # clone the repository
    git clone https://github.com/neherlab/pangraph.git && cd pangraph
    # build the package
    julia --project=. -e 'using Pkg; Pkg.build()'

The library can be accessed directly by entering the REPL:

    julia --project=.

Alternatively, command-line functionalities can be accessed by running the main src/PanGraph.jl script:

    # example: build a graph from E.coli genomes
    julia --project=. src/PanGraph.jl build -c example_datasets/ecoli.fa.gz > graph.json

Note that to access the complete set of functionalities, the optional dependencies must be installed and available in your $PATH.

Docker container

PanGraph is available as a Docker container:

    docker pull neherlab/pangraph:latest

See the documentation for extended instuctions on its usage.

Relocatable binary

pangraph can be built locally on your machine by running (inside the cloned repo)

    export jc="path/to/julia/executable" make pangraph && make install

This will build the executable and place a symlink into bin/. Importantly, if jc is not explicitly set, it will default to vendor/julia-$VERSION/bin/julia. If this file does not exist, we will download automatically for the user, provided the host system is Linux or MacOSX. Moreover, for the compilation to work, it is necessary to have MAFFT and mmseqs2 available in your $PATH, see optional dependencies.

Note, it is recommended by the PackageCompiler.jl documentation to utilize the officially distributed binaries for Julia, not those distributed by your Linux distribution. As such, compilation may not work if you attempt to do so.

Note, pangraph was developed in Julia v.1.7.2. Compatibility with more recent versions of Julia is not guaranteed.

Optional dependencies

pangraph can optionally use mash, MAFFT, mmseqs2 or fasttree for some optional functionalities, as explained in the documentation. For use of these functionalities, it is recommended to install these tools and have them available on $PATH.

Alternatively, a script bin/setup-pangraph is provided to install both tools into bin/ for Linux-based operating systems.

Examples

Please refer to the tutorials within the documentation for an in-depth usage guide. For a quick reference, see below.

Align a multi-fasta sequence.fa and realign each pancontig with MAFFT

	pangraph build sequence.fa | pangraph polish > graph.json

Export a graph graph.json into export/pangraph.gfa as GFA for visualization

	pangraph export graph.json

Compute all pairwise graphs and estimate parsimonious number of events between strains. Output all computed data to directory pairs

	pangraph marginalize graph.json -o pairs

Citing

PanGraph: scalable bacterial pan-genome graph construction Nicholas Noll, Marco Molari, Liam P. Shaw, Richard Neher Microbial Genomics 9.6 (2023); doi: https://doi.org/10.1099/mgen.0.001034

License

MIT License