Abstract
The COVID-19 pandemic has led to a rapid accumulation of SARS-CoV-2 genomes, enabling genomic epidemiology on local and global scales. Collections of genomes from resources such as GISAID must be subsampled to enable computationally feasible phylogenetic and other analyses. We present genome-sampler, a software package that supports sampling collections of viral genomes across multiple axes including time of genome isolation, location of genome isolation, and viral diversity. The software is modular in design so that these or future sampling approaches can be applied independently and combined (or replaced with a random sampling approach) to facilitate custom workflows and benchmarking. genome-sampler is written as a QIIME 2 plugin, ensuring that its application is fully reproducible through QIIME 2's unique retrospective data provenance tracking system. genome-sampler can be installed in a conda environment on macOS or Linux systems. A complete default pipeline is available through a Snakemake workflow, so subsampling can be achieved using a single command. genome-sampler is open source, free for all to use, and available at https://caporasolab.us/genome-sampler. We hope that this will facilitate SARS-CoV-2 research and support evaluation of viral genome sampling approaches for genomic epidemiology.
Highlights
The intersection of the SARS-CoV-2 outbreak and the genomics revolution has led to the rapid accumulation of viral genomes that are fueling our epidemiological understanding of the global pandemic
Resemblance to NextStrain context sequence sampling workflow The NextStrain workflow subsamples context sequences for its phylogenetic tree builds using augur and scripts in their ncov repository. Their workflow subsamples the context sequences across two axes: time and geography, prioritizing similarity to focal sequences when selecting sequences from different geographic regions
When determining the closest matches, percent identity is computed based on a multiple sequence alignment of all sequences, which is computed by aligning each sequence against a reference alignment using mafft[10]
Summary
Hope that this will facilitate SARS-CoV-2 research and support evaluation of viral genome sampling approaches for genomic epidemiology. This article is included in the Coronavirus collection. Testing and initial application of this software was performed on Northern Arizona University’s Monsoon computing cluster, funded by Arizona’s Technology and Research Initiative Fund. Additional analysis effort was funded under the State of Arizona Technology and Research Initiative Fund (TRIF), administered by the Arizona Board of Regents, through Northern Arizona University. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
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