nf-core is a community-driven initiative that provides a curated set of analysis workflows built using Nextflow . These workflows are designed to be scalable, reproducible, and standardised, ensuring high-quality bioinformatics analyses across different research domains. By fostering collaboration and best practices, nf-core helps streamline computational biology and genomics research.
GHGA collaborates with nf-core to develop, maintain and support the use of standardised bioinformatics workflows. Rather than creating new workflows independently, GHGA works with nf-core and other relevant communities to improve and adapt existing pipelines for genomic and phenotypic data processing. This ensures that GHGA’s workflows align with widely accepted community standards while remaining interoperable and efficient.
This collaboration helps to streamline our pipelines, avoid redundancy, enhances workflow sustainability, and supports a FAIR-compliant data analysis ecosystem. By integrating with nf-core, GHGA contributes to open science by improving workflow functionality and usability, making it easier for researchers to process genomic data in a secure and reproducible manner.
A recent publication, spearheaded by the Next Generation Sequencing Competence Network (NGS-CN) and GHGA, introduces NCBench, a platform for continuous benchmarking of genomic variant calling workflows.
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Participating actively in two conferences in September, CoRDI and GCB, GHGA members networked closely with the research data infrastructure and bioinformatics communities.
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The GHGA workflow workstream was involved in the release of bioinformatic workflows (sarek 3.0, nanoseq 3.0, and DROP 1.2), collaborating with the nf-core community and the Gagneur lab.
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