nf-core pipeline · extracellular-vesicles, ont
nf-core/evexplorer
A Nextflow pipeline for quality control, normalisation, and differential expression analysis of extracellular vesicle RNA.
What nf-core/evexplorer is
nf-core/evexplorer is a bioinformatics analysis pipeline designed for investigating RNA derived from extracellular vesicles. Extracellular vesicles carry small and diverse pools of RNA between cells, requiring tailored workflows for accurate processing and comparison across experimental groups.
Built within the nf-core framework, the pipeline supports multiple sequencing and library preparation technologies, including NEXTFLEX, comboSeq, and Oxford Nanopore Technologies (ONT). It manages the entire computational progression from initial read evaluation through to statistical analysis.
What the pipeline does
The workflow begins by running quality control on raw sequencing reads using FastQC, subsequently aggregating these quality metrics into a unified report with MultiQC.
Downstream stages process the sequencing data by identifying expressed genomic regions, carrying out library size normalisation, and executing differential RNA expression (DRE) analysis across samples.
Key facts
- Target analyte
- Extracellular vesicle RNA
- Supported technologies
- NEXTFLEX, comboSeq, Oxford Nanopore Technologies (ONT)
- Quality control tools
- FastQC, MultiQC
- Core analytical steps
- Read QC, expressed region detection, library size normalisation, differential RNA expression (DRE)
- Workflow framework
- Nextflow
What you can use it for
- Short-read vesicular RNA profiling
- Processing and assessing extracellular vesicle RNA datasets generated using NEXTFLEX or comboSeq library preparation protocols.
- Nanopore long-read vesicle sequencing
- Evaluating extracellular vesicle RNA read data generated via Oxford Nanopore Technologies sequencing.
- Comparative RNA quantification
- Normalising library sizes and detecting differentially expressed RNA regions between different vesicle conditions or sample cohorts.
Run it here
The research agent runs nf-core/evexplorer with Nextflow on its own machine — up to 32 cores, 256 GiB of memory and 24 hours per run, which covers the test profile and real single-sample runs. It builds the samplesheet, checks it against the pipeline's schema and reads the results back. When a run is too big for one machine, it gives you the exact command for your own cluster instead.
Strengths and limits
Good at
- Compatible with both short-read methods (such as NEXTFLEX and comboSeq) and long-read Oxford Nanopore Technologies data.
- Integrates raw read quality control using FastQC and consolidated reporting via MultiQC.
- Combines expressed region detection, library normalisation, and differential RNA expression within a single workflow.
Watch out for
- Support is limited to NEXTFLEX, comboSeq, and ONT technologies, with additional sequencing protocols pending future support.
- Pipeline-specific details for downstream parameter configuration and output metrics are minimally documented in the repository.
Questions
Can I run nf-core/evexplorer without my own cluster?
The research agent runs nf-core/evexplorer with Nextflow on its own machine — up to 32 cores, 256 GiB of memory and 24 hours per run, which covers the test profile and real single-sample runs. It builds the samplesheet, checks it against the pipeline's schema and reads the results back. When a run is too big for one machine, it gives you the exact command for your own cluster instead.
What licence is nf-core/evexplorer under?
MIT, like every nf-core pipeline.
Which sequencing technologies and library kits does the pipeline support?
It is compatible with NEXTFLEX, comboSeq, and Oxford Nanopore Technologies (ONT) datasets, with support for further protocols planned for future updates.
What tools are used for initial quality assessment?
Read quality evaluation is conducted using FastQC, and the resulting metrics are compiled into an overview report with MultiQC.
Can the pipeline detect differential expression?
Yes, it performs expressed region detection, normalises library sizes, and carries out differential RNA expression (DRE) analysis.
How to cite it
Philip Ewels, Alexander Peltzer, Sven Fillinger, Harshil Patel, Johannes Alneberg, Andreas Wilm, Maxime Ulysse Garcia, Paolo Di Tommaso & Sven Nahnsen. The nf-core framework for community-curated bioinformatics pipelines. Nat Biotechnol. 2020 Feb 13. doi: 10.1038/s41587-020-0439-x.
Written from nf-core/evexplorer's own README. Statements citing a figure that does not appear there are removed before publication. Licence and running details come from our registry.