Evidence map›Paper›PMID 40989335›Full record

ArticlePeerJ. Computer science2025

CFSAN SNP Pipeline 2 (CSP2): a pipeline for fast and accurate SNP distance estimation from bacterial genome assemblies.

Robert Literman, Jayanthi Gangiredla, Hugh Rand, James B Pettengill

Abstract read
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Article in PeerJ. Computer science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Clinical and molecular characteristics of Streptococcus agalactiae bacteremia in nonpregnant adults: a single-center analysis over 16 years in Hiroshima, Japan.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2026
    Article
  2. Probing Genomic Diversity ofFoods (Basel, Switzerland) · 2026
    Article
4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Robert LitermanHuman Foods Program-Office of Surveillance Strategy & Risk Prioritization-Division of Surveillance and Data Integration, United States Food and Drug Administration, College Park, Maryland, United States.
Jayanthi GangiredlaHuman Foods Program-Office of Laboratory Operations & Applied Science-Division of Food Safety Genomics, United States Food and Drug Administration, Laurel, Maryland, United States.
Hugh RandHuman Foods Program-Office of Surveillance Strategy & Risk Prioritization-Division of Surveillance and Data Integration, United States Food and Drug Administration, College Park, Maryland, United States.
James B PettengillHuman Foods Program-Office of Surveillance Strategy & Risk Prioritization-Division of Surveillance and Data Integration, United States Food and Drug Administration, College Park, Maryland, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Accurate genetic distance estimation from pathogen whole-genome sequence data is critical for public health surveillance, and with respect to food safety it provides crucial information within traceback and outbreak investigations. The computational demands required for contemporary bioinformatics pipelines to extract high resolution single nucleotide polymorphisms (SNPs) grow in parallel with the size of pathogen clusters, where single strains of common pathogens such as Methods: To facilitate rapid analysis of whole-genome sequencing (WGS) data for large clusters of foodborne bacterial pathogens, we introduce the CFSAN SNP Pipeline 2 (CSP2). CSP2 is a bioinformatics pipeline coded in Nextflow and Python that extracts SNPs directly from genome assemblies in seconds through rapid MUMmer whole-genome alignment and parallel processing. After genome alignment, most data processing steps mirror the quality control measures used in the CFSAN SNP Pipeline (CSP1), including density filtering and missing data handling. Results: Analysis of simulated data finds that high quality assemblies from the strategic K-mer extension for scrupulous assemblies (SKESA) contain sufficient information for accurate, high resolution SNP distance estimation, while assemblies from the St. Petersburg genome assembler (SPAdes) contained more false positives. CSP2 SNP distances for 150 real-world clusters (50 each of

Indexed as

BacteriaGenomicsPathogenSNP distance

Identifiers

PMID40989335
PMCPMC12453658

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