{"title":"AxioParse: streamlining Axiom Microbiome assay data processing and dataset generation.","authors":"Pranav Kirti, Pirooz Eghtesady, Mathieu Garand","doi":"10.1080/07366205.2026.2644218","DOIUrl":null,"url":null,"abstract":"<p><p>The Applied Biosystems Axiom Microbiome Array enables high-throughput detection of bacteria, archaea, viruses, protozoa, and fungi across multiple samples. However, its native software outputs are not compatible with common downstream analysis tools, requiring preprocessing. We identified a lack of open-source pipelines tailored to these outputs. To address this gap, we developed AxioParse, a Python-based pipeline built with the Dagster orchestration framework that automates data cleaning, taxonomic mapping, and formatting for downstream analysis. AxioParse reduces manual processing and generates datasets compatible with platforms such as QIIME2 and R, improving reproducibility and facilitating broader use of the Axiom Microbiome Array in microbiome research (https://github.com/Eghtesady-Lab-Bioinformatics/axioparse).</p>","PeriodicalId":8945,"journal":{"name":"BioTechniques","volume":"78 1-12","pages":"93-97"},"PeriodicalIF":2.5000,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"BioTechniques","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1080/07366205.2026.2644218","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2026/3/18 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
引用次数: 0
Abstract
The Applied Biosystems Axiom Microbiome Array enables high-throughput detection of bacteria, archaea, viruses, protozoa, and fungi across multiple samples. However, its native software outputs are not compatible with common downstream analysis tools, requiring preprocessing. We identified a lack of open-source pipelines tailored to these outputs. To address this gap, we developed AxioParse, a Python-based pipeline built with the Dagster orchestration framework that automates data cleaning, taxonomic mapping, and formatting for downstream analysis. AxioParse reduces manual processing and generates datasets compatible with platforms such as QIIME2 and R, improving reproducibility and facilitating broader use of the Axiom Microbiome Array in microbiome research (https://github.com/Eghtesady-Lab-Bioinformatics/axioparse).
期刊介绍：
BioTechniques is a peer-reviewed, open-access journal dedicated to publishing original laboratory methods, related technical and software tools, and methods-oriented review articles that are of broad interest to professional life scientists, as well as to scientists from other disciplines (e.g., chemistry, physics, computer science, plant and agricultural science and climate science) interested in life science applications for their technologies.
Since 1983, BioTechniques has been a leading peer-reviewed journal for methods-related research. The journal considers:
Reports describing innovative new methods, platforms and software, substantive modifications to existing methods, or innovative applications of existing methods, techniques & tools to new models or scientific questions
Descriptions of technical tools that facilitate the design or performance of experiments or data analysis, such as software and simple laboratory devices
Surveys of technical approaches related to broad fields of research
Reviews discussing advancements in techniques and methods related to broad fields of research
Letters to the Editor and Expert Opinions highlighting interesting observations or cautionary tales concerning experimental design, methodology or analysis.
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