This project aims to enhance the nf-core/ampliseq pipeline to support plant metabarcoding analyses. By expanding the reference database, we will improve its functionality, fostering broader adoption and making plant metabarcoding more accessible to the scientific community.

Goals

• Expanding the reference sequences for plant metabarcoding analyses.
  • For people who enjoy working with Nextflow and are interested in plant metabarcoding.
• Integrating the new references following the latest nf-core and Nextflow standards.
  • For people with some experience in (nf-core) workflow development.
• Benchmarking and validating the pipeline to ensure error-free performance.
  • For people with some experience in using Nextflow/nf-core pipelines.
• Improving documentation and user support to promote broader adoption.
  • For first-time contributors interested in making the pipeline more accessible!

We welcome contributors of all experience levels.

Group Leaders

Nikos Pechlivanis

Sofoklis Keisaris

This project focuses on creating an nf-core pipeline for processing data for cell painting analysis using CellProfiler, cytotable, pycytominer, and other tools.

Goals

• Fill out the basic documentation for the planned pipeline in the nf-core/cellpainting repo.
  • For people who are familiar with cell painting and would like to focus on the documentation.
• Add appropriate test data to nf-core/datasets for the pipeline.
  • For people who are familiar with cell painting and can identify data for use in unit tests.
• Create a module(s) for CellProfiler processing steps of the workflow including:
  • Z projection
  • QC
  • illumination correction
  • analysis
  • For people who are familiar Nextflow and nf-core module development.

We welcome contributors of all experience levels.

Group Leaders

Ken Brewer

Maxime Garcia

We are developing a Nextflow for HPC training for Australia’s national supercomputers, NCI’s Gadi HPC and Pawsey’s Setonix HPC. The training will be delivered in 2025 by the Australian BioCommons and partners. We intend to develop a hands-on workshop providing attendees with practical skills in configuring, optimising, and troubleshooting Nextflow pipelines on HPC systems. It will cover essential HPC job scheduling concepts, best practices for resource allocation, and efficient software environment management. This workshop will be extensible to other HPC systems, but initially will focus on targeting PBSPro and SLURM schedulers.

Goals

• Plan workshop structure and delivery mechanism
• Identify basic and advanced topics to be covered in workshop
• Develop learning objectives and lesson plan
• Note contributors and their roles in the workshop

We welcome contributors who have experience working on these systems and an interest in developing and delivering this training at their institution.

Group Leaders

Georgie Samaha

Fred Jaya

Giorgia Mori

This project aims to improve and optimize the nf-core/bacass pipeline by enhancing assembly strategies and exploring new analysis steps.

We will focus on:

1. Benchmarking and testing new tools to improve genome assembly strategies.
2. Focusing on long-read and hybrid assembly approaches to enhance the quality of results.
3. Identifying additional improvements discussed in this GitHub issue.

We welcome contributors of all experience levels.

Goal

1. Optimize assembly strategies by integrating and testing new tools.
2. Improve support for long-read and hybrid genome assembly.
3. Explore additional enhancements based on community discussions.

Group Leaders

Daniel Valle-Millares

This project aims to update and optimize the nf-core/bactmap pipeline as the last update to the pipeline was June 2021.

We will focus on:

1. Update to current nf-core template: current template is very out of date.
2. Update modules to current versions: many of the tools are old versions.
3. Potentially incorporating long read mapping as an option: would improve pipeline if ONT and PacBio could also be mapped
4. Update documentation: update documentation to reflect updates and improvements to pipeline
5. Identifying additional improvements: as discussed in GitHub issues.

We welcome contributors of all experience levels.

Goals

1. Update pipeline to current nf-core template and standards (intermediate experience).
2. Update all modules (beginner experience)
3. Add support for long-read mapping (intermediate experience).
4. Update documentation (beginner experience)
5. Explore additional enhancements based on community discussions (intermediate experience).

Group Leaders

Andries van Tonder

nf-core/clipseq has been inching towards a very massive feature-packed 2.0.0 release on the feat-2-0 branch. This would be a great opportunity to start crossing off tasks to get us over that sweet, sweet nf-core release line!

Tasks include:

• updating to the latest template,
• adding tests,
• improving documentation
• pipeline tube map

Goal

Work towards a dazzling 2.0 release.

Group Leaders

Charlotte Capitanchik

This project focuses on creating bioimage data processing modules based on OME tools and standards. These modules aim to provide initial support for large scale bioimage processing with OME-NGFF.

Goals

• Adding a new module for the bioformats2raw tool. See Bioformats, OME-Zarr
• Adding a new module for the raw2ometiff tool. See OME-TIFF
• Adding a new module for data transfer with OMERO (based on omero-py)

We welcome contributors of all experience levels.

Group Leaders

Sabrina Krakau

Luis Kuhn Cuellar

Carolin Schwitalla

Looking into making more packages build natively for linux/arm64 and improving performance of the important ones for faster and cheaper runs on ARM machines such as AWS Graviton.

Also - feel free to join if you would like any help in deploying and testing linux/arm64 software on your favourite pipelines, or performance and cost benchmarking!

See current progress and project board.

Goal

Optimise run time on at least one tool

Group Leaders

David Lecomber

nf-co2footprint plugin project

Resources

• Website
• Github
• Slack

Summary

Help us to solve problems we encountered during the path to the first release of a CO2 estimation plugin for Nextflow runs.

Goals

• Address open issues in of the current plugin development process
• Brainstorm for potential features

Tasks

• Add information on potential CO2 footprint optimization
  • Issue
• Accumulate CO2 Emission of several runs from cache
  • Issue
  • One value for included cached footprint, one for real execution value
• cpu_model comparison to vendor info
  • Issue
• Compare the Plugin results to the AWS Report
• Run plugin on AWS; make it applicable for AWS
  • Info about server and server location accessible?
  • Does AWS use special AWS servers?

Group Leaders

Sabrina Krakau

Josua Carl

Nadja Volkmann

This project aims to update, review, and release the version of the CoproID coprolite identification pipeline. With the last major release in 2020, CoproID version 2.0 is an entire rewrite of the original pipeline, with Meriam Van Os (@MeriamOs) as a major contributor.

Goals

• Try the rewrite of the pipeline (on the dev branch)
• Find bugs
• Merge dev into master
• Release 🎆

We welcome contributors of all experience levels.

Group Leaders

Maxime Borry

This project focuses on generating additional data, materials and automated tools to support bioinformatics education, and the use of Nextflow in academic curricula.

Goals

• Creating a pipeline to simulate educational datasets

  • This is for contributors with experience in nf-core module structure and dependencies, and ideally with experience in teaching bioinformatics at different levels. The purpose of the pipeline is to generate what we call “storyline-based data”, i.e. datasets which can follow a storyline and with a specific biological meaning to be identified when used for bioinformatics education.

• Translation of tutorials

  • For users who would like to contribute by translating existing tutorials in a language different than English.

• Domain specific tutorials

  • For users with experience using nf-core pipelines to analyse specific datasets, and who would like to contribute by identifying the appropriate simulated datasets, and creating a tutorial to guide new users in specific applications of a pipeline.

We welcome contributors of all experience levels, particularly in creating documentation and reviewing existing one.

Group Leaders

Francesco Lescai

Mariangela Santorsola

Project aim

We would like to expand nf-core/genomeqc with new tools and functionalities. Your ideas are very welcome!

Suggestions about documentation, code readability, or anything you can think of are also appreciated.

Goals

• Add FCS decontamination subworkflow:
  • Merge decontamination PR.
• Update template for nf-core/tools v3.2.0:
  • Merge update PR.
• Expand nf-core/genomeqc with new modules and workflows.
• Solve issues:
  • Check out the open issues. We will label good first issues for those less experienced with nf-core.
• Check first release PR:
  • Revise comments, commit suggestions.

Group Leaders

Fernando Duarte

Chris Wyatt

This project is intended to help anyone who needs help or advise with their illustration needs. This could be advise on how to create pipeline logos or tube maps or help with a conference poster that features nf-core.

Shout out in the #graphics Slack channel and we will find you someone to answer your questions.

Resources

• nf-core color guide
• nf-core font guidelines
• nf-core logo design guidelines
• nf-core workflow diagram guidelines

We welcome contributors of all experience levels.

Group Leaders

Franziska Bonath

Nicolas Vannieuwkerke

This group will focus on improving and optimizing the JSON schemas available in nf-core pipelines. Lots of JSON schemas lack keywords that could massively improve the validation of the pipeline input. The error messages are also very confusing and incomplete in most cases.

Everyone is welcome from absolute beginners to seasoned Nextflow/nf-core users.

We will also start migrating the last pipelines that are still using nf-validation to nf-schema as a secondary goal.

Goal

1. Improve and optimize JSON schemas in nf-core pipelines
2. (Optionally) Migrate more pipelines from nf-validation to nf-schema

Group Leaders

Nicolas Vannieuwkerke

This project aims to build upon and update the nf-core/lncpipe pipeline, originally designed for the analysis of long non-coding RNAs (lncRNAs). While development has slowed down, we aim to modernize the pipeline and bring it to the current nf-core and Nextflow pipeline standards, improve its usability, and demonstrate its relevance for the scientific community.

We welcome contributors of all experience levels.

Goals

1. Expand documentation and user support to encourage wider adoption.

   A great entry point for first-time contributors—help make the pipeline more accessible!

2. Update the pipeline to the latest nf-core and Nextflow standards.

   Perfect for those who enjoy working with Nextflow and want to contribute to pipeline modernization.

3. Improve compatibility with current reference genome annotations and transcriptomic datasets.

   A great challenge for contributors familiar with RNA-seq data and bioinformatics workflows.

4. Optimize integration with existing RNA-seq pipelines for seamless lncRNA analysis.

   Ideal for those with some experience in workflow development and RNA sequencing analysis.

Join us in improving lncpipe and making lncRNA analysis more accessible!

Group Leaders

Cris Tuñí-i-Domínguez

James Koltes

Eelco Meerdink

A pipeline for processing Illumina DNA Methylation array datasets: 450k, EPIC and EPICv2

Goals

1. tidy up whatever has been written now and write custom containers for the whole pipeline (3 processes for now)
2. attach the Dockerfile to the pipeline itself (cellranger in scrnaseq cannot be run with conda so I think this pipeline could rely on containers only until we find a fix)
3. scripts rely on the directory access/path rather than the file access/paths (difficulty in fetching the directory itself from the test-data repo: perhaps add module for creating the CSV file with the input path as the scripts currently are expecting it and align with the requirements for proper -profile test setup.
4. tidy up the R scripts and parametrize hardcoded options
5. add a disclaimer that this will not run with conda
6. update docs
7. coordinate if the output of the pipeline generates same results using previously analyzed projects (align with @Ghada Nouairia)
8. remove FastQC module and remove MultiQC module or add custom QC plots with versions to the report
9. currently two tests are failing on GitHub actions related to pipeline logos, but these pass the nfcore tools repo.

Motivation

Differential analysis of DNA methylation can come from sequencing reads, but also from Illumina methylation array which are for detecting methylation intensity at certain pre-programmed sites. This pipeline is for the latter technique as there already is a nf-core project for the former (methylseq).

Group Leaders

Adrian Janucik

Ghada Nouairia

Ramon Fallon

Introduction

MITNANEX is a pipeline designed for mitochondrial genome assembly and annotation from Nanopore sequencing data. It aims to provide a streamlined workflow for processing long-read mitochondrial sequencing data, from raw reads to a fully annotated mitochondrial genome.

By joining this group, you can:

1. Create a Docker container for all tools needed in the pipeline.
2. Automate the current pipeline in Nextflow to improve scalability and reproducibility.
3. Enhance documentation and usability to make the pipeline more accessible

This project is exclusively for onsite participants working in Medellín, Colombia.

Goal

• Work towards a first functional release with automated mitochondrial genome assembly, polishing, and annotation.
• Refactor the pipeline to follow nf-core best practices, ensuring modularity, scalability, and reproducibility.
• Bonus Develop an nf-core config for seamless integration with any Nextflow pipeline, allowing -profile to work out of the box.

Group Leaders

Jelena Pejovic

This project aims to make improvements to the existing nanoseq pipeline.

Goals

1. Improve existing nanoseq modules
2. Use nf-core modules where possible
3. Get pipeline to pass linting
4. Implement other nanoseq functionality that has yet to be added

Motivation

Many of us are Clinical Bioinformaticians and would like to see if we can improve and update nanoseq for potential clincal use with nanopore.

Group Leaders

Graeme Smith

Katie Williams

Some of us develop and maintain Nextflow pipelines that require ongoing maintenance. As these pipelines get updated, it’s crucial to ensure they continue working as intended.

We are running an nf-test working group during the hackathon where we collaborate on writing and applying unit tests to existing institutional pipelines.

Goals

• Explore the nf-test documentation and guides
• Identify and share minimal test datasets
• Apply and share tips for writing effective unit tests (Arrange, Act, Assert)

This is an opportunity to contribute to open-source Nextflow pipelines developed by Australian institutions while improving pipeline reliability and best practices.

We welcome contributors of all experience levels.

Group Leaders

Fred Jaya

Mitchell O'Brien

This project aims to finalise the transition of unit tests for all nf-core modules and sub-workflows to nf-test. It’s a good starting point for first timer to contribute and review Pull-Request.

Goal

1. Move all nf-core/modules to nf-test

• Batch 1
• Batch 2

2. Move all nf-core/subworkflows to nf-test

• Batch 1

More informations

• Pytest to nf-test migration documentation
• nf-test bitesize talk
• nf-test guidelines

How to proceed

As there are a lot of modules (i.e. 162) and subworkflows (i.e. 23) to migrate we need to stay organised to avoid duplicated work. To do so, we created three issues to track every contribution and a simple procedure as follows:

• Check if no one is already assigned to the modules/subworkflow you want to work on using one of the three main issues:
  • Modules Batch 1
  • Modules Batch 2
  • Subworkflows Batch 1
• Assign yourself to the sub-issue
• Perform the migration
  • Fork nf-core/modules repository to your Github account
  • Clone locally or use gitpod/codespaces
  • Clone pytest2nf-test git clone https://github.com/GallVp/pytest2nf-test
    • Install it ./gradlew installDist
    • Create alias or add to PATH: alias pytest2nf-test=${PWD}/build/install/pytest2nf-test/bin/pytest2nf-test
  • Go to modules repo and create a branch git checkout -b <tool_name>
  • Run pytest2nf-test --nfcore-modules <tool_name>
  • Run nf-core modules test <tool_name> -profile <singularity/docker/conda> and nf-core modules lint <tool_name>
  • Fix nf-test if necessary
  • Check if the module follows the guidelines
  • Commit changes and create Pull Request (PR) and link it to the sub-issue
• When your PR is ready, ask for a review and review someone else’s PR
• When merged update the Hackathon project
• Rinse and repeat!

Group Leaders

Louis Le Nézet

Thanks to the generous sponsorship from Nebius, we have access to 16 powerful H100 GPUs for the duration of this hackathon. Nebius is providing these resources through their Slurm-based workload manager called Soperator, enabling participants to test and develop GPU-accelerated tools with Nextflow using a familiar Slurm interface. We welcome people from all other projects to use these resources if they need access to GPUs.

To enable participants access to the Slurm cluster with the GPU resources, we need to add your public key to the authorized_keys list on the Slurm cluster. If you want access, please contact Florian with your public key.

You can create a dedicated ssh keypair with ssh-keygen like this, replacing the example email address with your own (store in a safe location):

ssh-keygen -t rsa -C "your_email@example.com"

Once your public key has been added to the authorized_keys list on the cluster, you can connect to it with:

ssh -i /path/to/your/private_key username@hostname

Goal

Use GPUs via Slurm to test and develop GPU accelerated tools in Nextflow and nf-core.

Group Leaders

Florian Wuennemann

Alexander Kim

This project aims to continue the development of the nf-test plugin nft-tiff for .tiff-files.

Goals

1. Implement exact matching for .tiff files (content and metadata).
2. Implement partial matching for .tiff files (e.g. x % agreement).

Motivation

The need for nft-tiff arose during the development of nf-core/rangeland, a pipeline that analyses satellite imagery. As the first earth observation pipeline in nf-core with a stable release, no off-the-shelf nf-test plugin for checking common earth observation file formats was available. The development of nft-tiff started at a previous hackathon. For this hackathon, we would like to bring nft-tiff closer to a full release. The development of this plugin will benefit future earth observation pipelines in nf-core and Nextflow as it supports a common file format in the field.

Tagged Image File Format (TIFF) and GeoTIFF

TIFF is a file format for storing multi-channel raster images. An important extension to the TIFF format is GeoTIFF. GeoTIFF extends the format with a variety of metadata fields relevant for geoscientific analysis (such as nf-core/rangeland).

Group Leaders

Felix Kummer

Tools like VIPER and ARACne from the Califano Lab are useful in understanding the protein-activity interactions, on an individual sample basis, from gene expression profile data:

“Under the premise that cellular phenotypes not only result from alterations in the genomic code but also depend on the influences of multiscale networks of molecular interactions that regulate gene expression, protein abundance, epigenetic state, and signaling activity. Therefore, understanding how the code embedded in the genome eventually generates cellular phenotypes requires the development of methods for integrating data describing these various levels of activity.” Source

Goal

Create modules and a subworkflow for the computational inference of protein activity network and its interactions, useful for precision medicine to understand how drugs are involved in protein pathways.

Group Leaders

Juan E. Arango Ossa

Dylan Domenico

Konstantinos Liossis

This project aims to get nf-core/hlatyping back on track.

Goals

1. Template update (last touched 2022 😬 )
2. Add new modules

• arcasHLA
• HLA-LA

We welcome contributors of all experience levels.

Group Leaders

Natasa Anastasiadou

Stella Fragkouli

Mark Polster

This project aims to begin work on the nf-core/proteinannotator pipeline.

Vision

Build the best protein annotator in the world.

Protein fasta -> ??? -> Profit!

• the ??? is nf-core/proteinannotator
• We want to build the pipeline of choice by the people sequencing the genomes of new creatures to annotate protein fasta files with function
• Future options include using synteny of genes, but that is beyond the 1.0.0 release

BEFORE WRITING ANY CODE, we will first draw out the metromap for the pipeline.

Similar pipelines

Below are pipelines that also process protein fasta files and add either functional or structural information to them, but don’t have exactly the same purpose as proteinannotator. We will likely use their modules.

• funcscan to search (meta)genomic nucleotide data for functional protein sequences, e.g. for biosynthetic gene clusters, antimicrobial peptide genes, and antimicrobial resistance genes
• reportho to compare ortholog predictions across methods
• proteinfamilies to cluster protein sequences into families, and updates existing families with new sequences
• proteinfold to fold protein sequences with ESMFold, AlphaFold2

Annotation Tools to Include

Please contribute more tools! This is just a starting point.

• DIAMOND-blastp
• InterProScan
• UniProt’s UniFire — Instructions
• FoldSeek — will require folding protein structures, e.g. with ESMFold2 or AlphaFold2

We welcome contributors of all experience levels.

Group Leaders

Olga Botvinnik

This project aims to work towards release 1.2.0 of the nf-core/proteinfold

Goal

• Adressing any open issue and open a PR.
  • For anyone interested.
• Finishing and merging any open PRs.
  • For people with some experience in Nextflow/nf-core pipelines.
• Final touches before release 1.2.0.
  • For people with experience with the pipeline.

We welcome contributors of all experience levels.

Group Leaders

Keiran Rowell

Ziad Al-Bkhetan

Patri Bota

Jose Espinosa-Carrasco

This project aims to close open PRs and issues of the nf-core/reportho pipeline to finalize release 1.1.0.

Goals

• Update custom report

We need to update the custom report to include the sequence-based merging step results (if run) and exclude alignment/phylogeny results. The code for this part is partially in a separate repo, so contact me before you work on this.

• Update MultiQC report

We need to make sure that the MultiQC report contains all required information and no more (i.e. no references to alignment or phylogeny).

• Update metro map

The workflow has changed since 1.0. We need to update the metro map to reflect that.

• Verify documentation

We need to verify that all documentation files are up to date. I have already made some changes, but there might be something missing.

• Finally, submit for review

Note

I will not be available on Monday (March 24). Feel free to work on your forks and submit PRs during that day. I will review all changes on Tuesday morning (CET).

We welcome contributors of all experience levels. Feel free to get in touch on the Slack channel if you have any questions or comments.

Group Leaders

Igor Trujnara

This project aims to make improvements to various existing RTG Tools modules, and add some new ones

Goals

1. Improve existing RTG Tools modules
2. Implement other RTG Tools functionality that has yet to be added

Motivation

We created RTG Tools so figure it would be good to contribute to the maintenance of the nf-core modules.

Group Leaders

Dan Jones

Jen Reeve

Project aim

We will work on nf-core/sammyseq, designed for the analysis of a brand-new NGS application to analyze the chromatin state. We want complete it by adding a new functionality: a Hi-C-like analysis of compartments, expand and improve the alignment / preprocessing part and update documentation accordingly. Any suggestions about documentation, code readability, usability and user-friendliness is warmly welcome. Open to contributors of all experience levels, tasks for beginners will be labeled “good first issue”.

Goals

• Add compartment analysis subworkflow and components
• Add bwa-mem alignment
• Update the schema figure (metro map) to accurately represent the current analysis workflow
• Solve as many open issues as we can
• Check what is needed for the first release

Group Leaders

Margherita Mutarelli

Ugo Maria Iannacchero

This project will work on improving the nf-core/sarek pipeline with a focus on maintenance like:

• Add nf-tests to subworkflows
• Improve input validation
• Improve documentation
• Update modules to latest tool version (sentieon, gatk,…)
• New additions welcome!

Goals

Improve sarek stability.

Group Leaders

Rike Hanssen

This project will work on adding a module to filter out genomic contaminants to the nf-core/sarek pipeline. This would be analogous to what is currently implemented in the nf-core/rnaseq pipeline with BBSplit. We will focus on implementing xengsort to do this. The steps here would be:

• finishing off the xengsort module
• making a subworkflow to run xengsort
• integrating this subworkflow into sarek

All skill levels welcome.

Goals

Introduce the filtering of genomic contaminants as a feature in the sarek pipeline.

Group Leaders

Asher Preska Steinberg

This project aims to enhance the nf-core/scdownstream pipeline for downstream scRNA-seq analysis. By expanding the range of available tools, we will improve its functionality, fostering broader adoption and making the pipeline more up-to-date and appealing to the scientific community.

Goals

• Expanding the range of doublet detection tools to include better-performing tools, particularly scDblFinder.

  • For people who have experience with scRNA-seq QC in Python or R
  • Based on benchmark comparisons, scDblFinder generally outperforms the currently listed tools.

• Expanding the range of cell type annotation tools to include other species currently not accounted for, particularly mice.

  • For people who have experience with mouse or other model organism’s scRNA-seq data analysis
  • Datasets like Tabula Muris (Senis) will be explored for support integration.

• Improving documentation and user support to promote broader adoption.

  • For first-time contributors interested in making the pipeline more accessible!

Contributors of all experience levels are welcome!

Group Leaders

Kurayi Chawatama

Emre Taha Çevik

nf-core/seqinspector aims to be a pipeline for initial quality control of sequencing data. Input is either FASTQ files or a run folder, and output is planned to be a global MultiQC report and, if wished, MultiQC files of groups that are defined in the sample sheet. By joining this group you can

1. Start with implementation of long read methods (advanced level, we have only limited experience in the group, so help would be more than appreciated!).
2. Work on display of the data in the MultiQC reports (beginner - intermediate level)
3. Write documentation

Goal

Work towards a first release.

Group Leaders

Franziska Bonath

The Single-cell Expression Atlas analysis workflow runs downstream analyses using Scanpy, leveraging the scanpy-scripts package to run individual steps of the Scanpy workflow.

See Single Cell Expression Atlas and current Nextflow workflow.

Goal

Adapting the Single-Cell Expression Atlas Analysis Workflow to meet nf-core standards.

Group Leaders

Pedro Madrigal

Iris Yu

Introduction

METASPACE is the cloud computing engine for annotating metabolites, lipids, and glycans in imaging mass spectrometry data, and hosts a knowledgebase of over 13.000 public annotated datasets from over 200 labs.

Most METASPACE users access the platform through the web app, which offers core functionalities for uploading, processing, and visualizing results.

However, bioinformaticians looking to integrate METASPACE into their workflows must develop custom scripts to interact with the METASPACE Python client and submit datasets.

Developing nf-core modules will streamline this process, enabling scalable and reproducible integration of METASPACE into existing bioinformatics pipelines.

This will also support METASPACE in-the-loop applications, particularly in spatial multi-omics integration workflows.

Goal

1. Create the following nf-core modules using Cardinal:

   1. Data import (creating MSImagingExperiment object).
   2. Preprocessing (Primarily peak picking) to generate a centroided dataset -> input for METASPACE.

2. Create an API module to submit datasets to METASPACE using METASPACE python client

3. Create a module to convert METASPACE datasets to AnnData and SpatialData objects using METASPACE Converter

4. Create a module to perform enrichment analysis using S2IsoMEr from AnnData object. (I’ll personally work on this module)

5. If time permits, combine the above modules in one pipeline

We welcome contributors of all experience levels. All of the above goals are suitable for beginners.

Group Leaders

Bishoy Wadie

This project aims to enhance the:

• nf-core/taxprofiler pipeline with a focus on the 1.3.0 - Crazy Corgi milestone
• nf-core/createtaxdb pipeline with a focus on the first release milestone

We welcome contributors of all experience levels.

Goals

1. Create modules for taxonomic classifiers (beginner friendly tasks):

• metacache
• metabuli
• melon

2. Add the classifiers to the taxprofiler workflow
3. (Optionally) Work on pipeline chaining approach
4. Add support for KMCP databases

Group Leaders

Sofia Stamouli

James Fellows Yates

This project aims to enhance and optimize the nf-core/viralrecon pipeline by addressing key issues and improving functionality, with a focus on the 2.7 milestone.

We welcome contributors of all experience levels.

Goal

1. Resolve codon merging issues to enhance sequence processing accuracy.
2. Improve Nanopore data analysis for better long-read handling.
3. Optimize MultiQC reporting to provide clearer and more comprehensive pipeline metrics.

Group Leaders

Sarai Varona

Let’s face it: we are not exactly a light-traveling company! Gathering everything a workflow needs for offline use results in a daunting packing list: the workflow itself, containerized software, configurations, plugins, Nextflow, Java, and more.

Fortunately, nf-core pipelines download is here to help with the packing. However, this sub-tool is due for some maintenance, refactoring, and code cleanup. As the final step in a long chain of dependencies, it must constantly adapt to the latest pipeline templates while ideally maintaining backward compatibility with older releases.

Navigating this nearly 2,000 lines codebase isn’t easy. But don’t worry — you’ll get a comprehensive introduction from an experienced “mountain” guide to help you scale this mountain of code. And if you’d like, we can even try pair-coding at times.

Goals

The full backlog - peek at your own risk ;-)

1. Amenable: Remove hard dependency on Singularity for better MacOS support, rather warn about incomplete container downloads.
2. Amenable: Improve container registry error messages: #2892
3. Advanced: Refactor WorkflowRepo class and remove SyncedRepo superclass: #2940. Get inspiration from here.
4. Advanced: Download plugins with the workflows: #3344
5. Ambitious: Wrap nextflow inspect and run on revised WorkflowRepo
6. Astounding: Move container downloads to a separate tool that is optionally called by nf-core pipelines download: #2408
7. Astounding: Support download/set-up of Docker containers as well see this post.
8. Audacious: Full multi-arch support for Seqera Containers #3179
9. Audacious: Download Galaxy Singularity containers through CVMFS support than via http: #18972

Who might like this project?

Feels like cheating, but is totally legal - dodge Nextflow at a Nextflow Hackathon and work with Python instead!

This project is perfect for participants looking to dip their toes into the nf-core ecosystem without diving deep into Nextflow itself! The nf-core tools are implemented in Python, making them an ideal entry point e.g. for scientists who already use the language to analyze their data and want to leverage their skills to contribute to nf-core.

This opportunity is for you if you’re more interested in deploying nf-core pipelines on various infrastructures rather than developing the workflows themselves. While contributing, you’ll gain valuable experience on the DevOps side of nf-core and learn how to deploy pipelines with confidence on your HPC. Your work will help make life easier for scientists worldwide who need to run pipelines in offline environments!

Group Leaders

Matthias Zepper