eDNAFlow, an automated, reproducible and scalable workflow for analysis of environmental DNA (eDNA) sequences exploiting Nextflow and Singularity
Metabarcoding of environmental DNA (eDNA) when coupled with high throughput sequencing is revolutionising the way biodiversity can be monitored across a wide range of applications. However, the large number of tools deployed in downstream bioinformatic analyses often places a challenge in configurat...
| Main Authors: | , , , , , , , , , |
|---|---|
| Format: | Journal Article |
| Language: | English |
| Published: |
Wiley-Blackwell
2021
|
| Subjects: | |
| Online Access: | http://hdl.handle.net/20.500.11937/86511 |
| _version_ | 1848764841701933056 |
|---|---|
| author | Mousaviderazmahalleh, Mahsa Mousavi Stott, Audrey Lines, Rose Peverley, Georgia Nester, Georgia Simpson, Tiffany Zawierta, Michal De La Pierre, Marco Bunce, Michael Christophersen, Claus |
| author_facet | Mousaviderazmahalleh, Mahsa Mousavi Stott, Audrey Lines, Rose Peverley, Georgia Nester, Georgia Simpson, Tiffany Zawierta, Michal De La Pierre, Marco Bunce, Michael Christophersen, Claus |
| author_sort | Mousaviderazmahalleh, Mahsa Mousavi |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Metabarcoding of environmental DNA (eDNA) when coupled with high throughput sequencing is revolutionising the way biodiversity can be monitored across a wide range of applications. However, the large number of tools deployed in downstream bioinformatic analyses often places a challenge in configuration and maintenance of a workflow, and consequently limits the research reproducibility. Furthermore, scalability needs to be considered to handle the growing amount of data due to increase in sequence output and the scale of project. Here, we describe eDNAFlow, a fully automated workflow that employs a number of state-of-the-art applications to process eDNA data from raw sequences (single-end or paired-end) to generation of curated and noncurated zero-radius operational taxonomic units (ZOTUs) and their abundance tables. This pipeline is based on Nextflow and Singularity which enable a scalable, portable and reproducible workflow using software containers on a local computer, clouds and high-performance computing (HPC) clusters. Finally, we present an in-house Python script to assign taxonomy to ZOTUs based on user specified thresholds for assigning lowest common ancestor (LCA). We demonstrate the utility and efficiency of the pipeline using an example of a published coral diversity biomonitoring study. Our results were congruent with the aforementioned study. The scalability of the pipeline is also demonstrated through analysis of a large data set containing 154 samples. To our knowledge, this is the first automated bioinformatic pipeline for eDNA analysis using two powerful tools: Nextflow and Singularity. This pipeline addresses two major challenges in the analysis of eDNA data; scalability and reproducibility. |
| first_indexed | 2025-11-14T11:25:46Z |
| format | Journal Article |
| id | curtin-20.500.11937-86511 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T11:25:46Z |
| publishDate | 2021 |
| publisher | Wiley-Blackwell |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-865112021-11-29T05:24:20Z eDNAFlow, an automated, reproducible and scalable workflow for analysis of environmental DNA (eDNA) sequences exploiting Nextflow and Singularity Mousaviderazmahalleh, Mahsa Mousavi Stott, Audrey Lines, Rose Peverley, Georgia Nester, Georgia Simpson, Tiffany Zawierta, Michal De La Pierre, Marco Bunce, Michael Christophersen, Claus Science & Technology Life Sciences & Biomedicine Biochemistry & Molecular Biology Ecology Evolutionary Biology Environmental Sciences & Ecology environmental DNA metabarcoding Nextflow Singularity Metabarcoding of environmental DNA (eDNA) when coupled with high throughput sequencing is revolutionising the way biodiversity can be monitored across a wide range of applications. However, the large number of tools deployed in downstream bioinformatic analyses often places a challenge in configuration and maintenance of a workflow, and consequently limits the research reproducibility. Furthermore, scalability needs to be considered to handle the growing amount of data due to increase in sequence output and the scale of project. Here, we describe eDNAFlow, a fully automated workflow that employs a number of state-of-the-art applications to process eDNA data from raw sequences (single-end or paired-end) to generation of curated and noncurated zero-radius operational taxonomic units (ZOTUs) and their abundance tables. This pipeline is based on Nextflow and Singularity which enable a scalable, portable and reproducible workflow using software containers on a local computer, clouds and high-performance computing (HPC) clusters. Finally, we present an in-house Python script to assign taxonomy to ZOTUs based on user specified thresholds for assigning lowest common ancestor (LCA). We demonstrate the utility and efficiency of the pipeline using an example of a published coral diversity biomonitoring study. Our results were congruent with the aforementioned study. The scalability of the pipeline is also demonstrated through analysis of a large data set containing 154 samples. To our knowledge, this is the first automated bioinformatic pipeline for eDNA analysis using two powerful tools: Nextflow and Singularity. This pipeline addresses two major challenges in the analysis of eDNA data; scalability and reproducibility. 2021 Journal Article http://hdl.handle.net/20.500.11937/86511 10.1111/1755-0998.13356 English Wiley-Blackwell restricted |
| spellingShingle | Science & Technology Life Sciences & Biomedicine Biochemistry & Molecular Biology Ecology Evolutionary Biology Environmental Sciences & Ecology environmental DNA metabarcoding Nextflow Singularity Mousaviderazmahalleh, Mahsa Mousavi Stott, Audrey Lines, Rose Peverley, Georgia Nester, Georgia Simpson, Tiffany Zawierta, Michal De La Pierre, Marco Bunce, Michael Christophersen, Claus eDNAFlow, an automated, reproducible and scalable workflow for analysis of environmental DNA (eDNA) sequences exploiting Nextflow and Singularity |
| title | eDNAFlow, an automated, reproducible and scalable workflow for analysis of environmental DNA (eDNA) sequences exploiting Nextflow and Singularity |
| title_full | eDNAFlow, an automated, reproducible and scalable workflow for analysis of environmental DNA (eDNA) sequences exploiting Nextflow and Singularity |
| title_fullStr | eDNAFlow, an automated, reproducible and scalable workflow for analysis of environmental DNA (eDNA) sequences exploiting Nextflow and Singularity |
| title_full_unstemmed | eDNAFlow, an automated, reproducible and scalable workflow for analysis of environmental DNA (eDNA) sequences exploiting Nextflow and Singularity |
| title_short | eDNAFlow, an automated, reproducible and scalable workflow for analysis of environmental DNA (eDNA) sequences exploiting Nextflow and Singularity |
| title_sort | ednaflow, an automated, reproducible and scalable workflow for analysis of environmental dna (edna) sequences exploiting nextflow and singularity |
| topic | Science & Technology Life Sciences & Biomedicine Biochemistry & Molecular Biology Ecology Evolutionary Biology Environmental Sciences & Ecology environmental DNA metabarcoding Nextflow Singularity |
| url | http://hdl.handle.net/20.500.11937/86511 |