LAGG

Looking at Genomes Graphically (LAGG) is a CLI tool for creating images from DNA sequences.

LAGG is capable of generating an image providing just an SRA (or ENA) accession number and a k-mer count. Of course, the CLI contains more options and even a config-based workflow for more complex processes.

Images are generated using an algorithm based on Chaos Game Representation¹ (CGR). This process creates images by counting k-mers for a genome / DNA sequence. With genomes aquired from the European Nucleotide Archive (ENA). Options are available to use Cutadapt² to preprocess the genomes before counting.

Installation

LAGG makes use of Jellyfish³ as a dependency for k-mer counting. Installation instructions can be found on the GitHub page for Jellyfish found here. Jellyfish is commonly available on major Linux distributions and on Homebrew for MacOS.

After installing dependencies, install LAGG using pip with the following command:

pip install pylagg

Usage

Using LAGG is as simple as executing the lagg command.

For example, to generate an image from an SRA or ENA accession number:

lagg cgr <accession> -k <kmer size>

Replace <accession> with any accession number (try DRR259113 for a small COVID-19 genome)

The <kmer_size> is an integer used when counting kmers which can eventually determine the size of the image. For larger genomes, consider a size of 9-10. For smaller ones, consider 5-8.

For more options or help type 'lagg --help or visit the documentation site here.

For Contributors

This project uses Poetry to handle dependencies and build the project. Installation instructions can be found here.

Install Dependencies

Similar to the CLI, Jellyfish is required to execute k-mer counting for LAGG. Please make sure to have to it installed before continuing. Instructions can be found in the "Installation" section above.

For project dependencies, use poetry install to automatically create a new virtual environment with all required packages.

If you'd like to install the dependencies directly within the project directory, use the following command:

poetry config virtualenvs.in-project true

Running Tests

To run tests, first, activate the virtual environment using poetry shell.

Use pytest to run all tests.