16S-Pipeline: A comprehensive web-based platform for end-to-end 16S rRNA amplicon sequencing analysis.

IF 3.8 4区 生物学 Q2 MICROBIOLOGY
Journal of Microbiology Pub Date : 2026-05-01 Epub Date: 2026-05-14 DOI:10.71150/jm.2603014
Tatsuya Unno
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引用次数: 0

Abstract

16S rRNA gene amplicon sequencing is the most widely used approach for characterizing microbial communities, yet analyzing such data requires navigating a fragmented landscape of bioinformatics tools with distinct installation requirements, parameter settings, and data formats. Here we present 16S-Pipeline, an open-source, web-based platform that provides a complete workflow from raw FASTQ files to publication-ready statistical analyses. 16S-Pipeline automatically detects sequencing type (paired-end, single-end, long-read), variable region, and sequencing platform (Illumina, PacBio HiFi, Nanopore), then performs quality filtering, primer trimming, amplicon sequence variant (ASV) inference via DADA2, taxonomy assignment against SILVA v138.1, phylogenetic tree construction, and optional functional prediction via PICRUSt2. Downstream analyses include alpha and beta diversity, taxonomic composition visualization, differential abundance testing using five complementary methods (ALDEx2, DESeq2, ANCOM-BC2, LinDA, MaAsLin2) with consensus reporting, and KEGG pathway mapping. Built-in NCBI SRA integration enables downloading public datasets for re-analysis and generates submission metadata spreadsheets for data deposition. The interactive web interface built on FastAPI and Plotly Dash enables researchers to perform complex microbiome analyses without command-line expertise. 16S-Pipeline is freely available at https://github.com/tatsu1207/16S-Pipeline under the MIT License.

16S- pipeline:基于web的端到端16S rRNA扩增子测序分析综合平台。
16S rRNA基因扩增子测序是表征微生物群落最广泛使用的方法,然而分析这些数据需要导航碎片化的生物信息学工具,这些工具具有不同的安装要求、参数设置和数据格式。在这里,我们介绍16S-Pipeline,这是一个基于web的开源平台,提供了从原始FASTQ文件到准备发布的统计分析的完整工作流程。16S-Pipeline自动检测测序类型(对端、单端、长读)、可变区域和测序平台(Illumina、PacBio HiFi、Nanopore),然后通过DADA2进行质量过滤、引物修剪、扩增子序列变异(ASV)推断、针对SILVA v138.1的分类定位、系统发育树构建和PICRUSt2的可选功能预测。下游分析包括α和β多样性、分类组成可视化、使用五种互补方法(ALDEx2、DESeq2、ANCOM-BC2、LinDA、MaAsLin2)进行差异丰度测试(具有共识报告)和KEGG通路映射。内置的NCBI SRA集成可以下载公共数据集进行重新分析,并生成提交元数据电子表格用于数据存储。基于FastAPI和Plotly Dash的交互式web界面使研究人员无需命令行专业知识即可执行复杂的微生物组分析。16S-Pipeline在MIT许可下可在https://github.com/tatsu1207/16S-Pipeline免费获得。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Microbiology
Journal of Microbiology 生物-微生物学
CiteScore
5.70
自引率
3.30%
发文量
0
审稿时长
3 months
期刊介绍: Publishes papers that deal with research on microorganisms, including archaea, bacteria, yeasts, fungi, microalgae, protozoa, and simple eukaryotic microorganisms. Topics considered for publication include Microbial Systematics, Evolutionary Microbiology, Microbial Ecology, Environmental Microbiology, Microbial Genetics, Genomics, Molecular Biology, Microbial Physiology, Biochemistry, Microbial Pathogenesis, Host-Microbe Interaction, Systems Microbiology, Synthetic Microbiology, Bioinformatics and Virology. Manuscripts dealing with simple identification of microorganism(s), cloning of a known gene and its expression in a microbial host, and clinical statistics will not be considered for publication by JM.
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