Related Experiment Video
Updated: Mar 19, 2026

A Method to Define the Effects of Environmental Enrichment on Colon Microbiome Biodiversity in a Mouse Colon Tumor Model
Published on: February 28, 2018
AxioParse: streamlining Axiom Microbiome assay data processing and dataset generation
Pranav Kirti1, Pirooz Eghtesady1, Mathieu Garand1
1Division of Pediatric Cardiothoracic Surgery, Department of Surgery, Washington University School of Medicine, St. Louis, MO, USA.
None:
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).
More Related Videos
09:52A Clinical Metaproteomics Workflow Implemented within Galaxy Bioinformatics Platform to Analyze Host-Microbiome Interactions Underlying Human Disease
Published on: January 10, 2025
09:29Using the Open-Source MALDI TOF-MS IDBac Pipeline for Analysis of Microbial Protein and Specialized Metabolite Data
Published on: May 15, 2019