ArticleF1000Research2019
MetaDEGalaxy: Galaxy workflow for differential abundance analysis of 16s metagenomic data.
Article in F1000Research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Increasing pathogenic germline variant diagnosis rates in precision medicine: current best practices and future opportunities.Human genomics · 2025Review
- Harnessing genomic technologies for one health solutions in the tropics.Globalization and health · 2024Review
- A Review of Web-Based Metagenomics Platforms for Analysing Next-Generation Sequence Data.Biochemical genetics · 2024Review
- Integrative meta-omics in Galaxy and beyond.Environmental microbiome · 2023Article
- Secreted and surface proteome and transcriptome ofFrontiers in parasitology · 2023Article
- A Practical Bioinformatics Workflow for Routine Analysis of Bacterial WGS Data.Microorganisms · 2022Article
- Administration of Hookworm Excretory/Secretory Proteins Improves Glucose Tolerance in a Mouse Model of Type 2 Diabetes.Biomolecules · 2022Article
- Bioinformatic Challenges Detecting Genetic Variation in Precision Medicine Programs.Frontiers in medicine · 2022Review
- Alterations and Prediction of Functional Profiles of Gut Microbiota After Fecal Microbiota Transplantation for Iranian RecurrentJournal of inflammation research · 2022Article
- A murine model of tuberculosis/type 2 diabetes comorbidity for investigating the microbiome, metabolome and associated immune parameters.Animal models and experimental medicine · 2021Article
- SHAMAN: a user-friendly website for metataxonomic analysis from raw reads to statistical analysis.BMC bioinformatics · 2020Article
- Gastrointestinal Helminth Infection Improves Insulin Sensitivity, Decreases Systemic Inflammation, and Alters the Composition of Gut Microbiota in Distinct Mouse Models of Type 2 Diabetes.Frontiers in endocrinology · 2020Article
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Authors and funding
5 authors.
Funding
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Abstract
Metagenomic sequencing is an increasingly common tool in environmental and biomedical sciences. While software for detailing the composition of microbial communities using 16S rRNA marker genes is relatively mature, increasingly researchers are interested in identifying changes exhibited within microbial communities under differing environmental conditions. In order to gain maximum value from metagenomic sequence data we must improve the existing analysis environment by providing accessible and scalable computational workflows able to generate reproducible results. Here we describe a complete end-to-end open-source metagenomics workflow running within Galaxy for 16S differential abundance analysis. The workflow accepts 454 or Illumina sequence data (either overlapping or non-overlapping paired end reads) and outputs lists of the operational taxonomic unit (OTUs) exhibiting the greatest change under differing conditions. A range of analysis steps and graphing options are available giving users a high-level of control over their data and analyses. Additionally, users are able to input complex sample-specific metadata information which can be incorporated into differential analysis and used for grouping / colouring within graphs. Detailed tutorials containing sample data and existing workflows are available for three different input types: overlapping and non-overlapping read pairs as well as for pre-generated Biological Observation Matrix (BIOM) files. Using the Galaxy platform we developed MetaDEGalaxy, a complete metagenomics differential abundance analysis workflow. MetaDEGalaxy is designed for bench scientists working with 16S data who are interested in comparative metagenomics. MetaDEGalaxy builds on momentum within the wider Galaxy metagenomics community with the hope that more tools will be added as existing methods mature.
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