ArticleBMC bioinformatics2017
16SPIP: a comprehensive analysis pipeline for rapid pathogen detection in clinical samples based on 16S metagenomic sequencing.
Article in BMC bioinformatics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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Who cites it
27 citing papers in PubMed.
- Host phylogeny and microbiome composition predict gut nematode community composition within a diverse assemblage of African herbivores.Biology letters · 2026Article
- The Potential of Bioinformatics in Revolutionizing Disease Diagnosis in Sub-Saharan Africa: A Narrative Review.Health science reports · 2026Article
- Associations Between Fine Particulate Matter-Associated Bacteria and Respiratory Tract Microbiota in Pigs.Animals : an open access journal from MDPI · 2026Article
- Role of wind in alteration of hilltop airborne bacterial communities enriched with pathogens over the Eastern Himalayas in India.Applied and environmental microbiology · 2026Article
- Identification of Opportunistic Pathogens on the Skin of Salamanders for Use as Molecular Targets of a De Novo Design of Multitarget Anti-International journal of microbiology · 2026Article
- Hotspots of Bacterial Pathogen Abundance and Exposure Risk in Soils of the Contiguous United States.GeoHealth · 2025Article
- NEMESISdb: A full length 16S rRNA gene dataset for the detection of human, fish, and crustacean potentially pathogenic bacteria.Data in brief · 2025Article
- Impact of virus-mediated bacterial interactions on acute gastroenteritis symptoms: A new scoring system for clinical assessment.Virulence · 2025Article
- Microplastic impacts archaeal abundance, microbial communities, and their network connectivity in a Sub-Saharan soil environment.FEMS microbiology ecology · 2025Article
- Role of artificial intelligence in cancer detection using protein p53: A Review.Molecular biology reports · 2024Review
- Deciphering the microbial communities in ticks of Inner Mongolia: ecological determinants and pathogen profiles.Parasites & vectors · 2024Article
- Ecology and risks of the global plastisphere as a newly expanding microbial habitat.Innovation (Cambridge (Mass.)) · 2024Article
- Characterization of pathogenic microbiome on removable prostheses with different levels of cleanliness using 2bRAD-M metagenomic sequencing.Journal of oral microbiology · 2024Article
- DCiPatho: deep cross-fusion networks for genome scale identification of pathogens.Briefings in bioinformatics · 2023Article
- Article
- Differential Oral Microbial Input Determines Two Microbiota Pneumo-Types Associated with Health Status.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2022Article
- Global airborne bacterial community-interactions with Earth's microbiomes and anthropogenic activities.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- Gut microbiome insights from 16S rRNA analysis of 17-year periodical cicadas (Hemiptera: Magicicada spp.) Broods II, VI, and X.Scientific reports · 2022Article
- Comparison of Propionibacterium genomes: CRISPR-Cas systems, phage/plasmid diversity, and insertion sequences.Archives of microbiology · 2022Article
- Microbial Community Analysis and Food Safety Practice Survey-Based Hazard Identification and Risk Assessment for Controlled Environment Hydroponic/Aquaponic Farming Systems.Frontiers in microbiology · 2022Article
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Authors and funding
6 authors.
Funding
Abstract
backgroundPathogen detection in clinical samples based on 16S metagenomic sequencing technology in microbiology laboratories is an important strategy for clinical diagnosis, public health surveillance, and investigations of outbreaks. However, the implementation of the technology is limited by its accuracy and the time required for bioinformatics analysis. Therefore, a simple, standardized, and rapid analysis pipeline from the receipt of clinical samples to the generation of a test report is needed to increase the use of metagenomic analyses in clinical settings.
resultsWe developed a comprehensive bioinformatics analysis pipeline for the identification of pathogens in clinical samples based on 16S metagenomic sequencing data, named 16SPIP. This pipeline offers two analysis modes (fast and sensitive mode) for the rapid conversion of clinical 16S metagenomic data to test reports for pathogen detection. The pipeline includes tools for data conversion, quality control, merging of paired-end reads, alignment, and pathogen identification. We validated the feasibility and accuracy of the pipeline using a combination of culture and whole-genome shotgun (WGS) metagenomic analyses.
conclusions16SPIP may be effective for the analysis of 16S metagenomic sequencing data for real-time, rapid, and unbiased pathogen detection in clinical samples.
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