Bioinformatics pipelines, built together.

Bioxflow is an open community for developing, reviewing and sharing reproducible analysis pipelines — from raw reads to results.

Browse pipelines →Start building

$ nextflow run bioxflow/rnaseq -profile test,docker

Runs the Bulk RNA-seq pipeline on its bundled test data. About this pipeline →

6
Pipelines in the catalogue
6
Analysis areas
2
Workflow engines
100%
Open source

Pipelines

What the community is building

View all 6 pipelines →

bioxflow/wgs

In development

Whole-genome sequencing

Read quality control, trimming, alignment and variant calling for whole-genome sequencing data.

wgsalignmentvariants
FastQC · fastp · BWA-MEM2 · SAMtoolsNextflow

bioxflow/rnaseq

Released

Bulk RNA-seq

FASTQ to differential expression. Every sample is quantified twice, by Salmon and by STAR, and the two results are compared before DESeq2 runs.

rna-seqgene-expressiondeseq2concordance
View pipeline →GitHubv1.0.0
fastp · Salmon · STAR · DESeq2 · MultiQCNextflow

bioxflow/amr

In development

Antimicrobial resistance genomics

Assembly and annotation of bacterial genomes with detection of resistance genes, virulence factors and mobile elements.

amrbacteriaannotation
AMRFinderPlus · ABRicate · Prokka · BLASTNextflow

How it works

From idea to released pipeline

  1. 1

    Propose

    Suggest a pipeline and agree on its scope with the community before writing code.

  2. 2

    Build

    Start from the Bioxflow template: modular processes, containers and a standard layout.

  3. 3

    Review

    Community review and automated tests check that results are correct and reproducible.

  4. 4

    Release

    Versioned releases with documentation, test data and citable outputs.

Why Bioxflow

Pipelines you can trust and reuse

Reproducible

Every step runs in a pinned Docker, Singularity or Conda environment, so results match across machines.

Portable

Run the same pipeline on a laptop, an HPC cluster or the cloud by switching one profile.

Standardised

A shared template, parameter schema and folder structure make every pipeline feel familiar.

Tested

Continuous integration runs each pipeline on small test datasets for every change.

Documented

Usage guides, parameter references and output explanations come with every release.

Community-led

Developers, researchers and students design and maintain pipelines together.

Have a pipeline in mind?

Join developers and researchers building the next generation of open, reproducible analysis pipelines.

Contribute a pipelineJoin the community