ArticleNature communications2016
Sequence element enrichment analysis to determine the genetic basis of bacterial phenotypes.
Article in Nature communications, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 124 papers, 2 of them syntheses that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
124 citing papers in PubMed, 2 syntheses or guidelines pooled it, 223 citations in OpenAlex.
- Pooled it
- Evaluation of parameters affecting performance and reliability of machine learning-based antibiotic susceptibility testing from whole genome sequencing data.PLoS computational biology · 2019Pooled it
- GeneScanner: profiling genetic variation across bacterial populations.Microbial genomics · 2026Article
- k-mer-based approaches to unlock genebank genomics for targeted crop improvement.Nature genetics · 2026Review
- BaGPipe: an automated, reproducible, and flexible pipeline for bacterial genome-wide association studies.BMC microbiology · 2026Article
- Genome-wide association study of Mycoplasma anserisalpingitidis strains for antibiotic susceptibility.Scientific reports · 2026Article
- Genomic and Phenotypic Bases of Salt Tolerance in Sinorhizobium meliloti: Candidate Traits for Bioinoculant Development Addressing Saline Soils.Microbial biotechnology · 2026Article
- Bacterial Systematic Genetics and Integrated Multi-Omics: Beyond Static Genomics Toward Predictive Models.International journal of molecular sciences · 2025Review
- Advancing microbial risk assessment: perspectives from the evolution of detection technologies.NPJ science of food · 2025Review
- Bacterial genome-wide association studies: exploring the genetic variation underlying bacterial phenotypes.Applied and environmental microbiology · 2025Review
- Reversible excision of the wzy locus in Salmonella Typhimurium may aid recovery following phage predation.PLoS genetics · 2025Article
- aurora: a machine learning gwas tool for analyzing microbial habitat adaptation.Genome biology · 2025Article
- Genome analysis of colistin-resistantFrontiers in microbiology · 2025Article
- An alignment- and reference-free strategy usingMycology · 2025Article
- Using GWAS and Machine Learning to Identify and Predict Genetic Variants Associated with Foodborne Bacteria Phenotypic Traits.Methods in molecular biology (Clifton, N.J.) · 2025Review
- Unitig-centered pan-genome machine learning approach for predicting antibiotic resistance and discovering novel resistance genes in bacterial strains.Computational and structural biotechnology journal · 2024Article
- Seamless, rapid, and accurate analyses of outbreak genomic data using splitGenome research · 2024Article
- Genome-based model for differentiating between infection and carriageMicrobiology spectrum · 2024Article
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64 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors at 8 institutions in 4 countries.
Funding
Abstract
Bacterial genomes vary extensively in terms of both gene content and gene sequence. This plasticity hampers the use of traditional SNP-based methods for identifying all genetic associations with phenotypic variation. Here we introduce a computationally scalable and widely applicable statistical method (SEER) for the identification of sequence elements that are significantly enriched in a phenotype of interest. SEER is applicable to tens of thousands of genomes by counting variable-length k-mers using a distributed string-mining algorithm. Robust options are provided for association analysis that also correct for the clonal population structure of bacteria. Using large collections of genomes of the major human pathogens Streptococcus pneumoniae and Streptococcus pyogenes, SEER identifies relevant previously characterized resistance determinants for several antibiotics and discovers potential novel factors related to the invasiveness of S. pyogenes. We thus demonstrate that our method can answer important biologically and medically relevant questions.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.