SNP-sites: rapid efficient extraction of SNPs from multi-FASTA alignments

By Andrew J. Page, Ben Taylor, Aidan J. Delaney, Jorge Soares, Torsten Seemann, Jacqueline A. Keane, Simon R. Harris. bioRxiv, 2016

1,379 citations recorded by the source corpus.

Rapidly decreasing genome sequencing costs have led to a proportionate increase in the number of samples used in prokaryotic population studies. Extracting single nucleotide polymorphisms (SNPs) from a large whole genome alignment is now a routine task, but existing tools have failed to scale efficiently with the increased size of studies. These tools are slow, memory inefficient and are installed through non-standard procedures. We present SNP-sites which can rapidly extract SNPs from a multi-FASTA alignment using modest resources and can output results in multiple formats for downstream analysis. SNPs can be extracted from a 8.3 GB alignment file (1,842 taxa, 22,618 sites) in 267 seconds using 59 MB of RAM and 1 CPU core, making it feasible to run on modest computers. It is easy to install through the Debian and Homebrew package managers, and has been successfully tested on more than 20 operating systems. SNP-sites is implemented in C and is available under the open source license GNU GPL version 3.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/b7b4399cdf6bd17645a696b03366431b685abc5c

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Citations in the corpus

Structural and Functional Analysis of the D614G SARS-CoV-2 Spike Protein Variant (2020, neutral): “5.1 Page et al., 2016 https://sanger-pathogens.github.io/ snp-sites/ EPU 2 software for single particle analysis Thermo Fisher Scientific N/A Other Quantifoil Au grid Quantifoil, Großlöbichau Germany N/A GloQube Plus Glow Discharge System Quorumtech N/A Vitrobot Mark IV Thermo Fisher Scientific…”
ARIBA: rapid antimicrobial resistance genotyping directly from sequencing reads (2017, methodology): “Repeats and prophages in the FA1090 genome were masked from the alignment before variable sites were identified with snp_sites [47] and a neighbour joining phylogenetic tree created with RapidNJ [48].”
GenSLMs: Genome-scale language models reveal SARS-CoV-2 evolutionary dynamics (2022, background): “Since the reward function is episodic, at each step of beam search, the highest scoring beams are chosen with This scoring modification effectively alters the likelihood of tokens to be sampled based on maximizing the reward function.”